AI Engineer jobs in Israel

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Key Responsibilities • AI solution development: Build and deploy AI tools and workflows using platforms such as Copilot Studio, UiPath, and other automation frameworks. • Integration & enablement: Connect AI agents with enterprise systems (e.g., SharePoint, M365), external APIs, and knowledge bases for seamless interoperability. • Process automation: Identify repetitive tasks and design intelligent automation to improve efficiency. • Security & identity integration: Secure agent interactions via encryption, authentication, and authorization; integrate with identity platforms (OAuth2, OIDC, SAML, Entra ID, AD FS) for access control. • Governance & compliance: Partner with cybersecurity on data protection and threat modeling, ensuring solutions meet security, ethical, and compliance standards. • Collaboration & training: Enable AI literacy across teams through best-practice documentation and internal training. • Continuous improvement: Collect feedback, iterate, and contribute to a culture of innovation and scale. Required Qualifications • Education: Bachelor's or master's in computer science, AI, machine learning, data science, or a related field, or equivalent related experience. • Experience: 5+ years in software development, including 2+ years in AI/ML engineering. • AI & automation foundations: Strong grasp of AI concepts, ML pipelines, and automation tools; hands-on with Copilot Studio, UiPath, and SharePoint. • Agentic & context engineering: Multi-agent workflows for complex tasks; context management via RAG, semantic chunking, and memory persistence; MCP-based context-aware systems including prompt engineering and context-window optimization; agent orchestration and A2A (agent-to-agent) systems. • Cloud & integration: Cloud AI platforms (Azure AI Foundry, AWS Bedrock, and/or Google Vertex AI), API integrations, and data-quality validation. • Development languages: .NET, C#, Python, Java, API development, SQL, PowerShell, Unix shell scripting. • Ways of working: Strong problem-solving, fast-paced agile delivery, and cross-team communication. Preferred Qualifications • Generative AI & agents: Exposure to generative AI, prompt engineering, or agent-based systems. • Governance & responsible AI: Interest in AI governance, security, and ethical frameworks. Delivery mindset: Adapts quickly and delivers quick wins while maintaining enterprise standards. About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all. With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM, NAND, and NOR memory and storage products through our Micron® brand. Every day, the innovations that our people create fuel the data economy, enabling advances in artificial intelligence and 5G applications that unleash opportunities — from the data center to the intelligent edge and across the client and mobile user experience. To learn more, please visit micron.com/careers All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. To request assistance with the application process and/or for reasonable accommodations, please contact [email protected] Before uploading your CV to apply for this position, please review our Applicant Privacy Notice and Employment Privacy Notice. Micron recruiters use review tools to identify your unique skill set based on the information in your CV, to inform the recruiter of skills you may have that are not listed on your CV (based on your career history and work experience), to supplement the information provided in your CV with information obtained from publicly accessible professional-oriented sources (such as your publicly available LinkedIn profile) and to assess how closely your skill set matches the defined skill set for this position. While submitting your CV through this platform is not obligatory, we encourage you to do so. If you do not want to benefit from the skill and qualification matching features, then you should not upload your CV through this platform. Instead, email your CV to [email protected] along with the Req Id number listed in the job description. Your CV will be forwarded to the appropriate recruiter for review. Micron Prohibits the use of child labor and complies with all applicable laws, rules, regulations, and other international and industry labor standards. Micron does not charge candidates any recruitment fees or unlawfully collect any other payment from candidates as consideration for their employment with Micron. AI alert: Candidates are encouraged to use AI tools to enhance their resume and/or application materials. However, all information provided must be accurate and reflect the candidate's true skills and experiences. Misuse of AI to fabricate or misrepresent qualifications will result in immediate disqualification. Fraud alert: Micron advises job seekers to be cautious of unsolicited job offers and to verify the authenticity of any communication claiming to be from Micron by checking the official Micron careers website in the About Micron Technology, Inc.

We're building an agentic AI platform that helps enterprises transform complex business workflows into AI-powered operations. We work with leading global companies to identify high-value workflows, deploy AI agents into real business environments, and help organizations move from experimentation to measurable enterprise impact. We believe AI adoption inside the enterprise isn't just a technology challenge. It requires business context, workflow understanding, change management, trust, ownership, and a clear path to value. That's where this role comes in. We are a well-funded, early-stage startup, looking for a talented and motivated AI Engineer to join our team. The focus of this role is to develop advanced AI agents aimed at automating and optimizing low-skill human tasks, with a special emphasis on document processing, data extraction, text and email comprehension, and related workflows. You will be responsible for researching, designing, and deploying AI solutions that can replace repetitive manual tasks, improving efficiency and scalability for organizations. Your Impact AI Agent Development • Design, develop, and implement AI agents using best of breed LLMs to automate document processing tasks across enterprise workflows. Workflow Automation • Build machine learning pipelines to automate content-heavy processes for enterprise businesses. Model Optimization • Fine-tune and optimize pre-trained LLMs to accurately interpret, classify, and process large volumes of documents, improving speed and accuracy. Collaboration • Partner with product, engineering, and business teams to identify high-value automation opportunities and integrate AI-driven solutions into our operations. Evaluation & Testing • Develop metrics and conduct extensive testing to ensure reliability and efficiency of the AI systems in real-world scenarios. What It Takes Experience • 5+ years of experience as a software engineer or data scientist building production systems. • 2+ years of experience with large language models and NLP techniques. • Background in developing AI agents for content heavy tasks. • Experience with multiple LLM Vendors, RAG or Fine Tuning OSS or Commercial models. Technical Skills • Proficiency in Python and machine learning libraries such as TensorFlow or PyTorch. • Deep understanding of LLM architectures and NLP applications like entity recognition, document classification, and summarization. • Experience with model grounding techniques, retrieval-augmented generation (RAG), and deploying robust AI models in production environments. • Skills in designing and deploying AI models through APIs, containerization (Docker, Kubernetes), and cloud platforms (AWS, GCP, Azure). • Understanding of best practices for continuous monitoring, evaluation, and iterative improvement of deployed models.

Description We're transforming how software gets built, with GenAI at the center of the development lifecycle. As an AI Transformation Engineer, AI transformation is your day-to-day focus. You'll design and build the agentic workflows, tools, and AI infrastructure our engineering teams rely on. You'll also take on business projects that need hands-on AI development, so the work stays varied. We're looking for a highly technical engineer who takes ownership of open-ended challenges, leads independently, and delivers results that move the needle. What You'll Do • Drive AI transformation across the SDLC: design, build, and ship agentic workflows for planning, coding, testing, code review, and security remediation, from prototype through production • Lead business-driven AI projects when needed, from understanding the product need to delivering the solution • Find what's worth automating: work with engineering teams, architects, and product managers to find high-impact use cases • Engineer the harness: design and manage agent context, knowledge, tools, and scaffolding, and build evals that keep agents reliable at scale • Own outcomes, not just tasks: turn broad goals into clear metrics such as adoption, throughput, cycle time, and quality, and show what your work moved Requirements • 5+ years of hands-on software engineering experience (TypeScript/Node.js, Java or Python) • Hands-on experience building and shipping LLM-powered systems or agentic workflows in production • Strong harness engineering skills: hands-on with Claude Code, GitHub Copilot, or similar tools, with a deep understanding of how to build, scaffold, and manage agent context at scale • Working knowledge of LLMs, RAG, tool use, MCP, evaluations, and human-in-the-loop patterns • Solid experience with CI/CD, GitHub Actions, and cloud platforms, preferably Azure • Proven ability to lead independently, bring structure to open-ended problems, and deliver measurable results • Highly technical, yet not afraid to dig into the product and understand the business side • Lives and breathes AI: stays current on the latest models, tools, and practices, and brings new ideas to the team • Strong communication skills and a team-player mindset Advantages: • Experience developing AI-SDLC / AI-PDLC solutions • Experience building a company brain or organizational knowledge layer at scale • Experience building agent verification solutions at scale, such as automated E2E testing with Maestro or similar frameworks • Proven track record of leading cross-team projects and aligning stakeholders with different priorities • Experience with agent orchestration frameworks, agent factories, or multi-agent systems • Familiarity with observability tooling for monitoring agent and platform health Why You'll Love Working With Us • Real impact at scale: what you build changes how an entire organization develops software • GenAI at the core: we don't just use AI, we build it into our engineering DNA • Learning & growth culture: every engineer has a personal professional growth plan We are hiring for various positions within the company, with some roles offered through outsourcing. Join us and enjoy a dynamic and flexible work environment.

AI Platform & Innovation Engineer We are looking for a Senior AI Platform & Innovation Engineer to join the AI Engineering Group in Tel Aviv. This role is focused on designing and building the foundational AI platform that powers next-generation AI capabilities across Nexxen’s products and engineering teams. You will help shape our AI strategy by building reusable platform capabilities, evaluating emerging AI technologies, and developing production-grade AI systems that enable developers, products, and business teams across the company. What You’ll Do • Design and build reusable AI platform capabilities used across multiple products. • Architect and implement production-grade agentic systems, including multi-agent workflows, tool orchestration, memory and planning capabilities. • Design and build internal AI platforms such as organizational knowledge (“Brain”), AI developer tools, autonomous engineering workflows, and shared AI services. • Research, evaluate and integrate emerging AI models, frameworks and developer tools into the platform. • Collaborate closely with Data Science teams to transform research into scalable production-ready AI capabilities. • Design end-to-end AI architectures, from data ingestion and retrieval to orchestration, model integration and production deployment. • Build and operate production AI services using modern cloud-native technologies. • Improve the reliability, scalability and observability of AI systems. • Define engineering standards, reusable patterns and best practices for AI development across engineering teams. • Lead technical proof-of-concepts and drive adoption of innovative AI technologies. • Mentor engineers and provide technical leadership on complex AI initiatives. What You’ll Bring • B.Sc. in Computer Science or a related field. • 5+ years of backend software engineering experience. • 3+ years of hands-on experience building production AI systems. • Strong Python development experience – Must. • Hands-on experience with Kubernetes, Docker and deploying production workloads in cloud-native environments – Must. • Hands-on experience with CI/CD pipelines, GitOps workflows and modern software delivery practices – Must. • Deep understanding of Large Language Models (LLMs), prompting, reasoning techniques, structured outputs, tool calling and retrieval architectures – Must. • Strong experience designing and building end-to-end AI systems, from data ingestion and orchestration to production deployment. • Experience designing AI agents, agentic workflows or AI automation systems. • Experience working with Data Science or Machine Learning teams. • Strong software architecture and distributed systems design skills. • Experience with vector databases, graph databases or modern AI data platforms – an advantage. • Experience with AI frameworks such as LangGraph, OpenAI Agents SDK, CrewAI, Semantic Kernel, AutoGen or similar – an advantage. • Experience evaluating and integrating emerging AI technologies into production systems – an advantage. • Excellent spoken and written English skills. • A proactive, curious and collaborative mindset, with a passion for building AI platforms and driving technical innovation across engineering teams. What if I have any questions before I apply? All applications need to be submitted online, however, to discuss any adjustments you may require ahead of submitting your application, please email [email protected] #LI-DK1 #LI-HYBRID At Nexxen, we value our differences, varied experiences, and collective contribution. We know that not everyone takes the same career path, so if you don’t match this job description perfectly, don’t worry! We would rather see your application than risk missing out on your potential to make an impact. For information about how we handle your personal information please view our Applicant and Candidate Privacy Notice Important Notice from Nexxen: Your Safety Matters At Nexxen, we care about the well-being of our current and future employees. We are aware of the growing number of online scams and fraudulent job postings, and we urge all job seekers to remain vigilant. Please be advised that Nexxen will never request payment (whether in cash, cryptocurrency, or any other form) as a condition of employment, offer positions that require you to invest in vague or dubious financial schemes, or promote roles that resemble get-rich-quick opportunities. If you receive a suspicious message claiming to be from Nexxen or encounter a questionable job posting associated with our name, please contact us at [email protected] to verify its legitimacy. Your trust is important to us. Stay safe and informed. Nexxen Fraud Alert and Notice: Protect Yourself from Impersonation and Fraudulent Activity

Description We are looking for a highly technical, hands-on Quality Engineering Lead to drive product quality through AI-powered automation, intelligent testing, and proactive issue detection. Your mission is to build and continuously improve automated quality mechanisms that identify bugs, regressions, performance issues, and unexpected system behavior before they impact our customers. You will leverage AI agents, modern development tools, and engineering automation to make quality an integral and continuous part of our development lifecycle. This is a senior, hands-on technical leadership role with ownership of the Quality Engineering domain across R&D. You will define the technical direction, lead cross-team initiatives, and establish the foundations for a scalable, AI-driven quality engineering function, with the opportunity to build and lead a dedicated team as the domain evolves. We are looking for someone who combines strong software engineering expertise, a passion for product quality, and the leadership skills to drive meaningful change across the engineering organization. Responsibilities • Build AI-Powered Quality Agents: Design and implement agents that proactively identify bugs, regressions, and unexpected behavior across our systems. • Develop Intelligent Testing Mechanisms: Build automated testing solutions that leverage AI to generate, execute, and maintain meaningful test scenarios. • Proactive Issue Detection: Analyze logs, metrics, traces, production behavior, and code changes to identify potential quality issues. • Automate Regression Detection: Develop mechanisms that continuously validate system behavior and detect regressions introduced by new releases. • Improve Release Confidence: Build automated quality gates and validation mechanisms integrated into CI/CD pipelines. • Production Quality Monitoring: Develop intelligent mechanisms that detect functional inconsistencies, data integrity issues, and unexpected production behavior. • AI-Assisted Root Cause Analysis: Build tools and agents that investigate detected issues, identify likely causes, and provide actionable findings to engineering teams. • Drive Quality Engineering Across R&D: Collaborate with all engineering teams to identify quality gaps, establish best practices, and drive the adoption of AI-powered quality mechanisms throughout the development lifecycle. • Technical Leadership & Ownership: Own and lead the Quality Engineering domain across R&D. Define the technical direction, drive cross-team initiatives, establish engineering standards, and mentor engineers working on quality-related solutions. • Build and Scale the Quality Engineering Function: Establish the technical foundations, processes, and tools needed to scale quality engineering across the organization, with the potential to build and lead a dedicated team. • Own Quality Improvements End-to-End: Independently design, develop, deploy, and maintain quality engineering tools and automation, ensuring measurable improvements in product quality. Requirements • 7+ years of hands-on software engineering, quality engineering, or test infrastructure development experience. • Proven technical leadership experience as a Tech Lead, Staff Engineer, or equivalent, with the ability to drive cross-team initiatives and influence engineering practices. • Strong programming skills in Python, TypeScript, or similar languages. • Extensive experience building automated testing frameworks, quality validation systems, or engineering automation infrastructure. • Hands-on experience using LLMs, AI coding tools, or AI agents to solve engineering problems. • Strong understanding of backend systems, APIs, distributed architectures, and cloud environments. • Experience with CI/CD pipelines, integration testing, and automated regression testing. • Strong debugging, troubleshooting, and root cause analysis skills. • Ability to define technical direction, mentor engineers, and take ownership of an engineering domain across the organization. • Strong communication and collaboration skills, with the ability to work effectively across multiple engineering teams. • Ability to independently identify quality gaps and deliver production-ready engineering solutions. Nice to Have • Experience building autonomous AI agents or agent-based testing frameworks. • Experience with Claude Code, Cursor, Codex, or similar tools. • Experience with Kubernetes, AWS, and microservices architectures. • Experience with observability platforms such as Datadog, Groundcover, or Grafana. • Experience with performance testing, chaos engineering, or production validation. • Familiarity with MCP, LLM tool calling, and agent orchestration. • Experience establishing or leading quality engineering initiatives across multiple development teams. • Experience building or scaling engineering teams or technical functions. What Success Looks Like • Critical bugs and regressions are detected before reaching customers. • Automated quality mechanisms continuously validate product behavior across development and production environments. • AI agents reduce manual testing, debugging, and investigation efforts. • Engineering teams receive actionable quality findings early in the development cycle. • Release confidence increases while maintaining or improving development velocity. • Product quality improves through measurable reductions in escaped defects and recurring incidents. • Quality engineering becomes a shared, AI-powered capability adopted across all R&D teams. • A scalable quality engineering function is established, with clear technical ownership, standards, and long-term direction. Our Vision Build an engineering organization where quality is continuously and proactively validated through intelligent automation and AI agents. • We believe quality should not depend solely on manual testing or reactive bug fixing. Our goal is to create an AI-driven quality engineering function that continuously identifies problems, prevents regressions, and empowers every engineering team to deliver reliable software faster.

About Fundamental Fundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict. At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI. Key responsibilities • Take part in development and optimization of a large neural network-based tabular model implemented in Python • Profile training and inference pipelines to identify performance bottlenecks • Rewrite critical components in Rust (via PyO3 or custom extensions) where Python limits us, with C++ (via PyBind11 or custom extensions) as a secondary option where appropriate • Improve memory efficiency, latency, and throughput across model pipelines • Ensure correctness, numerical stability, and reproducibility as the model evolves • Collaborate with ML researchers on productionizing new capabilities • Maintain clean abstractions, comprehensive tests, and clear documentation • Shape architectural decisions for our ML systems handling tabular data Must have • Strong software engineering fundamentals with expert-level Python and Rust • Hands-on experience bridging Python and Rust (PyO3, maturin, or custom extensions) • Experience developing and maintaining ML models in production • Strong understanding of neural networks • Track record of optimizing performance-critical code • Strong profiling and debugging skills (CPU, memory, latency) Nice to have • Experience with tabular ML approaches (transformers, tree/NN hybrids, learned embeddings) • Working proficiency in C++ and experience bridging Python and C++ (PyBind11, Cython, or custom extensions) • Familiarity with PyTorch internals or writing custom ops (Rust or C++) • Experience optimizing training loops, data pipelines, or inference engines • Background in numerical computing or systems programming • Exposure to large-scale ML infrastructure (distributed training, batching, caching) • Experience with the Rust async ecosystem (tokio) or SIMD/parallelism crates (rayon, ndarray) Benefits • Competitive compensation with salary and equity • Comprehensive health coverage for you and your dependents • Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys • Relocation support for employees moving to join the team in one of our office locations • A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

Description Gloat is the AI-native system of action for workforce orchestration. Our agentic HR platform lets enterprises build intelligent workforce agents that understand their people, respect their policies, and work where teams already are — Microsoft Teams, Slack, Google Chat, and Copilot, with no new portal or change management. The platform is powered by Loomra, our semantic layer that connects people, jobs, and skills through a knowledge graph, deep HCM integration (Workday, SuccessFactors, Oracle HCM), a governance engine, and semantic retrieval — with a full audit trail behind every agent decision. Trusted by 100+ enterprises across 112 countries, empowering 5M+ employees. This role sits at the center of that effort. We're looking for a Senior AI Engineer to design, build, and ship production-grade LLM agents that reason over workforce and skills data on top of Loomra's semantic layer. You won't just prototype — you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily (Teams, Slack, Copilot), and iteration in front of enterprise customers. You'll work alongside product, data, and platform engineers to turn powerful capabilities into reliable, safe, and fast product experiences. If you've built agents that actually made it to production — and you care as much about evaluation, guardrails, and reliability as you do about capability — we want to talk to you. Responsibilities • Design and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents. • Implement retrieval and RAG pipelines over structured and unstructured workforce data, grounded in our knowledge graph connecting people, jobs, and skills. • Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows. • Build evaluation harnesses, guardrails, and safety/bias checks, and work within the governance engine so agents behave reliably, respect customer policies, and produce a full audit trail. • Ship agents in a model-agnostic way across providers (Anthropic, Google, IBM watsonx) and deploy them into Teams, Slack, and Copilot. • Optimize agents for latency, cost, and reliability at enterprise scale. • Take agents from prototype to production — with monitoring, observability, and a fast iteration loop. • Partner closely with product, data, and platform teams to translate customer needs into agent capabilities. Requirements • 5+ years building production software • Proven experience building and shipping LLM agents to production — not just demos or prototypes. • Hands-on with at least one agent orchestration framework (e.g. LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or similar). • Strong Python and solid software engineering fundamentals. • Prompt engineering paired with systematic, measurable evaluation of LLM outputs. • Experience with tool use / function calling and integrating LLMs with external systems. • Track record deploying, monitoring, and maintaining AI in production (cloud, CI/CD, observability). Nice to Have • 2+ years hands-on with LLMs / generative AI. • Practical experience with RAG, embeddings, and vector databases (e.g. pgvector, Pinecone, or similar) • Experience with MCP, agent memory, and planning/reasoning patterns. • Background in HR tech, people data, or skills ontologies. • Knowledge graph / graph ML experience (knowledge graphs, GNNs). • Responsible AI: bias evaluation, guardrails, and AI governance. • Experience working across multiple model providers (e.g. Anthropic, Google, IBM watsonx) rather than a single vendor.

Description Gloat is the AI-native platform powering the era of Agentic HR. Powered by Loomra, our context engine is purpose-built for the workforce. Gloat lets you build any Agentic HR agent that operates in the flow of work across Slack, Microsoft Teams, Copilot, and Google Chat. Talent Redeployment, internal mobility, skills intelligence, workforce redesign, and whatever comes next. Trusted by leading global enterprises, Gloat serves over 1.5 million employees across 30+ Fortune 500 companies, unlocking more than 4.8 million strategic work hours. We help organizations harness AI to unlock agility, productivity, and growth, empowering them to achieve true ROI and drive exponential productivity. About the Role We are looking for a highly driven and experienced AI Engineer Team Leader to manage and mentor a core team of engineers while remaining 50% hands-on. In this critical role, you will lead the development of our enterprise Agentic AI platform, blending deep technical expertise in AI agent development with strong engineering leadership. As a Team Leader, you will drive the technical agenda, plan sprints, and collaborate closely with Product Managers and cross-functional partners to turn powerful capabilities into reliable, safe, and fast product experiences. You must thrive in a high-pressure, dynamic startup environment characterized by a fast pace and frequent pivots, ensuring your team remains focused, agile, and aligned with business goals while executing at the highest level. You won't just manage - you'll own agent workflows end to end, from design through evaluation, deployment into the tools employees use daily, and iteration in front of enterprise customers. Responsibilities • Team Leadership & Management (50%): Manage, mentor, and grow a team of AI and software engineers. Oversee task allocation, sprint planning, and daily agile ceremonies. • Hands-On Engineering (50%): Actively code, design, and build multi-agent systems and orchestration - intent routing, planning, tool use, and coordination across specialized agents. • Technical Strategy & Architecture: Drive the technical agenda, architecture decisions, and best practices for developing scalable, LLM-driven applications grounded in our knowledge graph. • System Integration: Integrate LLMs with tool/function calling and protocols such as MCP to give agents controlled access to HCM systems, business logic, and workflows. • Production Excellence: Build evaluation harnesses, guardrails, and safety/bias checks. Optimize agents for latency, cost, and reliability at enterprise scale. Take agents from prototype to production - with monitoring, observability, and a fast iteration loop. • Cross-Functional Collaboration: Work intimately with Product Management, Data, and Design teams to translate customer needs into agent capabilities, define roadmaps, and prioritize tasks. • Agility & Execution: Lead the team through frequent pivots and rapid development cycles, ensuring high-quality delivery under pressure in a fast-paced startup environment. Requirements Must-Have: • 2+ years of experience managing or leading a high-performing software/AI engineering team. • 5+ years of hands-on experience as a Backend or AI/Software Engineer building complex, scalable distributed systems in production. • Proven hands-on experience building and shipping LLM agents to production - not just demos or prototypes. • Hands-on with at least one agent orchestration framework (e.g. LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, or similar). • Strong Python and solid software engineering fundamentals. • Strong agile project management skills with a track record of effective sprint planning and execution. • Demonstrated ability to thrive in a dynamic, high-pressure startup environment with rapid execution and frequent shifts in direction. • Excellent communication skills, with the ability to build strong partnerships with Product Managers and other stakeholders. Nice-to-Have: • 2+ years hands-on with LLMs / generative AI. • Practical experience with RAG, embeddings, and vector databases (e.g. pgvector, Pinecone, or similar). • Experience with tool use / function calling and integrating LLMs with external systems. • Experience with MCP, agent memory, and planning/reasoning patterns. • Responsible AI: bias evaluation, guardrails, and AI governance.

Description Accelerate Your Career in Cybersecurity! Pentera is the market leader in AI-native Security Validation, equipping enterprises with the platform to proactively test their defenses against the latest cyber attacks. Pentera proves which exposures are truly exploitable across the entire attack surface and drives remediation workflows that reduce real risk. Anchored in real-attack validation, the Pentera platform powers the full Continuous Threat Exposure Management (CTEM) cycle, from exposure discovery through prioritization, validation, and mobilization. Thousands of security teams around the world trust Pentera to close their security gaps before threat actors can exploit them. With over 350 team members and 1,300 customers in more than 60 countries, Pentera is a growing company supported by top investors such as Insight Partners, K1, and The Blackstone Group. If you want to grow your skills, make an impact, and be part of an innovative team, Pentera is the place for you. About the role: Pentera, a security company, is building an internal AI capability across the organization: agents that perform real tasks as the organization, with ROI and security assessed at every step. We are looking for a senior engineer who owns this end to end - a hands-on builder who also carries the senior function: setting the technical strategy, making the architecture calls, and being the person leadership trusts on internal AI. This is not a pure IC build role and not a pure strategy role. You will personally build the flagship systems - production agents, the context layer, the evaluation and safety stack - while also deciding what gets built, in what order, and to what standard. You will work across R&D, IT, Security, BizOps, Customer, Sales, Marketing, People, and Finance, with the AI Transformation Officer owning the business portfolio. What you'll do - strategy and senior function: • Own the technical strategy for Pentera's internal AI transformation: target architecture, model and vendor choices, build-vs-buy calls. • Shape the AI portfolio: which workflows to automate, in what sequence, with what success metrics - and push back when the wrong thing is being built. • Set and enforce the bar on ROI and security for every AI system: cost, adoption, cycle-time impact, access control, and auditability are reviewed per project, not after launch. • Act as the senior technical voice for internal AI: advise leadership, review AI initiatives across the org. • Turn one-off builds into a real internal platform: reusable patterns, shared services, and standards that AI Champions and teams adopt. • Mentor AI Champions; raise the org's practical AI level. • Manage Pentera's AI- Champions Community. • Continuously evaluate models, vendors, and frameworks, and keep Pentera agile. What you'll do - hands-on build: • Personally design, build, deploy, and own the flagship internal agents and AI workflows, from prototype through production. • Build and evolve Pentera's AI context layer: connectors, APIs, retrieval services, metadata, identity and authorization, controls, and tool interfaces. • Create safe action tools for agents and infrastructure for agents to work. • Build RAG, tool-calling, structured-output, and multi-step agentic workflows using the right model and architecture for each problem. • Own the production quality bar for what you ship: evaluation datasets and automated checks (accuracy, groundedness, task completion, safety, cost etc.) • Work directly with business owners to map processes, test with users, and drive each pilot to a clear scale-or-stop decision. Requirements • 4+ years of production software engineering, including strong Python, APIs, testing, CI/CD, data contracts, and cloud services. Applied and agentic AI is a new field - nobody has a decade of it - so we weight demonstrated ownership and depth over years: what you shipped, what you owned end to end, how deep you went. • Evidence of operating at senior scope, wherever you earned it: you have set technical direction, made architecture calls that others built on, and carried systems end to end - as a staff/lead engineer, a first AI hire, or similar. • Executive fluency: you turn ambiguous business needs into a technical plan, explain trade-offs simply to non-engineers, and say no with reasoning when needed. • Ownership mindset: you measure whether the system changed the business process, not whether the demo ran. Advantages: • Experience as a first or early AI hire, or standing up an internal AI platform or function. • Product management experience. • Experience building internal platforms or company-wide data products. We are an equal opportunity employer and we are committed to building a diverse and talented workforce. We do not discriminate on the basis of race, sex, religion, colour, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, medical condition, disability, or any other class or characteristic protected by applicable law. We welcome candidates from all backgrounds to join us!

We are seeking a AI Engineer to join our team and implement advanced AI solutions in our travel and expense management products. The ideal candidate will have strong backend engineering expertise and enthusiasm for working with cutting-edge AI technologies. You'll be responsible for designing and implementing backend services that integrate AI capabilities including large language models (LLMs), retrieval-augmented generation (RAG), and conversational interfaces into our consumer-facing products. This is an opportunity to expand your expertise into AI while leveraging your strong engineering foundation. What You’ll Do • Design and develop scalable, high-performance backend services and APIs. • Implement integrations with AI platforms and services. • Work with AI specialists to translate AI capabilities into production-ready features. • Ensure high reliability, performance, and security of AI-powered systems. • Collaborate with product and engineering teams to gather requirements and deliver solutions. What We’re Looking for: • 5+ years of professional backend engineering experience. • Strong proficiency in at least one backend programming language (Java etc). • Experience building and maintaining production-grade APIs and microservices. • Solid understanding of distributed systems, data structures, and algorithms. • Experience with SQL and NoSQL databases. • Track record of delivering consumer-facing products at scale • Experience with AI/ML platforms and services (OpenAI, Hugging Face, etc.) • Familiarity with LLMs, RAG, or conversational AI. • Knowledge of vector databases and embedding technologies. • Experience with cloud platforms (AWS, GCP, Azure). • Understanding of AI/ML concepts and implementation patterns. Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers. Human oversight: Metaview does not automatically reject candidates or make final hiring decisions. Our recruiters and hiring managers review all outputs and make the final hiring decision regarding every application. • Your rights: If you prefer to have your application reviewed without AI assistance, you may request a human evaluation by entering your email here. Your decision to do so will not affect how your candidacy is evaluated. Please refer to our Candidate Privacy Notice for more information about our processing of personal data, and your rights.

Description Sygnia is a top tier cyber technology and services company, providing high-end consulting and incident response support for organizations worldwide. Sygnia works with companies to proactively build their cyber resilience and to respond and defeat attacks within their networks. It is the trusted advisor and cyber security service provider of IT and security teams, senior managements, and boards of top organizations worldwide, including Fortune 100 companies. The company draws on top talent from the ranks of elite military technology units and from across the cyber industry and has some of the world’s top talents in cybersecurity. Described by Forbes as a “cyber security delta force”, it applies technological supremacy, digital combat experience, data analytics and a business-driven mindset to cyber security, enabling organizations to excel in the age of cyber. Our Technology division builds a world class product, considered by experts as the leading XDR platform for cyber analytics and investigations. Our product was deployed in hundreds of clients, including many Fortune 500 companies, all around the world (from North America through Europe, APAC and all the way to Australia), and as a part of the team you will have the privilege to take part in the ongoing fight against cyber threat actors of the highest levels. We are looking for a talented, passionate, and experienced Senior GenAI Engineer to join our team. You will design and build production-grade GenAI applications from the ground up, using technologies such as Google ADK, Docker, and AWS (Bedrock, AgentCore etc). We’re looking for someone with a genuine passion for GenAI, strong software engineering skills, hands-on experience developing GenAI solutions, and a collaborative, hands-on approach. You will also work closely with the team’s researchers, helping transform research code and prototypes into reliable, secure, and scalable containerized applications that can be deployed and operated in the cloud. Main Responsibilities: • Design and development of production-grade GenAI applications and agentic systems • Build and operate reliable, secure, and scalable AI-powered services, with a focus on performance, observability, and cost • Drive engineering best practices, including testing, evaluation, CI/CD, code review, and technical design, while contributing to product and technical innovation • Work closely with the team’s researchers to transform research code and prototypes into reliable, containerized applications that can be deployed and operated in the cloud Requirements Main Requirements: • 5+ years of software engineering experience building production systems • 3+ years of professional Python development experience • Hands-on experience designing and developing production GenAI applications • Strong understanding of LLMs, agentic systems, RAG, tool calling, prompt engineering, and evaluation • Experience using GenAI observability tools for tracing, monitoring, evaluating, optimizing and debugging AI applications • Strong experience with Docker and cloud environments (preferably AWS). • Strong coding standards and experience with testing, CI/CD, observability, and production troubleshooting • Strong communication skills and the ability to clearly articulate technical ideas and trade-offs • High proficiency in English, both written and spoken • A collaborative, responsible team player with a genuine passion for GenAI and continuous learning Advantage: • Hands-on experience with Google ADK • Experience defining AWS infrastructure using AWS CDK • Experience with AWS GenAI services such as Amazon Bedrock and Amazon Bedrock AgentCore • Experience developing AI solutions for cybersecurity or security products

Location: Kfar Saba, IL (hybrid ERGO NEXT's mission is to help entrepreneurs thrive. We’re doing that by building the only technology-led, full-stack provider of small business insurance in the industry, taking on the entire value chain and transforming the customer experience. Simply put, wherever you find small businesses, you’ll find ERGO NEXT. Since 2016, we’ve helped hundreds of thousands of small business customers across the United States get fast, customized and affordable coverage. We’re backed by industry leaders in insurance and tech, and we still have room to grow — that’s where you come in. We are seeking a product-minded AI Engineer to design, build, and ship end-to-end AI-driven capabilities to our system. The role focuses on rapid execution, pragmatic product and business awareness, and full-stack ownership in a fast-paced, highly dynamic environment. What You’ll Do: • Build AI-driven applications and features end-to-end, including any task necessary (UI, light devOps, data cleanups, etc.) required to achieve successful delivery. • Work with internal stakeholders and product teams to translate raw, shifting requirements into clear technical solutions. • Leverage 100% Agentic Coding workflows to maintain exceptional development velocity and capability. • Diagnose and resolve issues across the entire feature stack with a strong bias for action. • Apply critical thinking to separate essential business value from noise, actively identifying risks and challenging requirements when appropriate. What We Need: • 5+ years of meaningful software engineering experience. • Proven experience of delivering software to customers and a willingness to work on any part of the tech stack. • Daily proficiency with Agentic Coding approach (e.g., Cursor, Claude, Codex, etc.). • High comfort level with ambiguity, dynamic environments, and self-directed execution. • Strong communication skills and a pragmatic, product-first approach to problem-solving. • Hybrid Work Model: This role supports a flexible hybrid work model, requiring a minimum of three days per week on-site in the office, per company policy. Advantage • Hands-on experience developing LLM applications (most notable: Evaluations and RAG). • Background as an early-stage startup employee, founder, or active side-project builder. Note on Fraudulent Recruiting We have become aware that there may be fraudulent recruiting attempts being made by people posing as representatives of ERGO NEXT Insurance. These scams may involve fake job postings, unsolicited emails, or messages claiming to be from our recruiters or hiring managers. Please note, we do not ask for sensitive information via chat, text, or social media, and any email communications will come from the domain @next-insurance.com or @nextinsurance.com. Additionally, Next Insurance will never ask for payment, fees, or purchases to be made by a job applicant. All applicants are encouraged to apply directly to our open jobs via the careers page on our website. Interviews are generally conducted via Zoom video conference unless the candidate requests other accommodations. If you believe that you have been the target of an interview/offer scam by someone posing as a representative of Next Insurance, please do not provide any personal or financial information. You can find additional information about this type of scam and report any fraudulent employment offers via the Federal Trade Commission's website (https://consumer.ftc.gov/articles/job-scams), or you can contact your local law enforcement agency. Don’t meet every single requirement? Studies have shown that some underrepresented people are less likely to apply to jobs unless they meet every single qualification. At ERGO NEXT, we are dedicated to building a diverse, inclusive and respectful workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. One of our core values is 'Play as a Team'; this means making sure everyone has an equal chance to participate and make a difference. We win by playing together. ERGO Next Insurance is an equal opportunity employer and prioritizes building a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants of any type and do not discriminate based on race, color, religion, national origin, gender, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job-related characteristics or other prohibited grounds specified in applicable federal, state, and local laws. ERGO Next's policy is to comply with all applicable laws related to nondiscrimination and equal opportunity and will not tolerate discrimination or harassment based on any of these characteristics. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Description At Classiq Technologies, we’re shaping the future of quantum computing. Our mission is to make quantum computing practical and impactful by bridging the gap between hardware and real-world applications. Our platform enables developers and enterprises to design, optimize, and deploy quantum algorithms at scale, automating complex processes and supporting teams from beginners to experts across diverse architectures. Classiq is trusted by Fortune 500 leaders and global governments. We accelerate the quantum era with a platform that transforms bold quantum ideas into working applications. We're looking for someone to make Classiq AI-native. You'll build agentic systems that do real SDLC work, find the bottlenecks in our processes and build the AI tooling that removes them. Agentic pipelines, internal tools, whatever the work demands. High ownership and a direct say in what gets built next. What you'll do • Own the SDLC pipeline: ticket sync → planning → implementation → PR • Design agentic systems: prompts, tools, evals, guardrails, human-in-the-loop approvals, cost/latency tradeoffs • Build integrations across Jira, GitHub, Figma, and LLM providers • Own the roadmap, rollout, and adoption of internal AI tooling Who you are • 5+ years of relevant professional experience • BSc degree in Computer Science, Software Engineering, Physics, Mathematics, or a related field. • Strong TypeScript/Node and/or Python • Production LLM/agent experience: tool calling, orchestration, context pipelines, evals • Ability to own a workstream from requirements through iteration and drive adoption without a team under you Bonus points • durable workflows (Restate/Temporal), React internal tools, agent tooling (Claude Code, Cursor, MCP), Kubernetes/Datadog, interest in quantum. Stack • TypeScript/Python, Restate, PostgreSQL, Anthropic/Bedrock/LiteLLM, Jira & GitHub APIs, AWS, Terraform. Requirements Who you are • 5+ years of relevant professional experience • BSc degree in Computer Science, Software Engineering, Physics, Mathematics, or a related field. • Strong TypeScript/Node and/or Python • Production LLM/agent experience: tool calling, orchestration, context pipelines, evals • Ability to own a workstream from requirements through iteration and drive adoption without a team under you Bonus points • durable workflows (Restate/Temporal), React internal tools, agent tooling (Claude Code, Cursor, MCP), Kubernetes/Datadog, interest in quantum. Stack • TypeScript/Python, Restate, PostgreSQL, Anthropic/Bedrock/LiteLLM, Jira & GitHub APIs, AWS, Terraform.

About Unframe Unframe is an AI-first startup helping the world’s largest enterprises bring LLM-powered applications to life in days - not months. We combine the speed of a product company with the flexibility of a consultancy, helping Fortune 500 companies move from idea to production faster than anyone else in the market. Backed by Bessemer, Craft, and TLV Partners with $50M in Series A funding, we’re building a fast-growing, revenue-generating company working with some of the biggest enterprises in the world. About the Role We're looking for an exceptional AI Engineer who sees the bigger picture - someone who can understand how entire teams and departments operate and fundamentally improve the way they work through AI and automation. You'll work across the organization to identify inefficiencies, rethink complex processes, and design and build AI-powered systems that drive meaningful operational change. This is a highly autonomous, hands-on role. We need someone who doesn't wait for requirements but identifies opportunities, takes ownership, and turns ambitious ideas into production-ready solutions. Your mission: Make Unframe dramatically more efficient, scalable, and AI-native. What You'll Do • Analyze and transform end-to-end workflows across departments, identifying opportunities for AI-driven automation and improvement. • Design and build sophisticated AI agents, multi-agent systems, and automation workflows. • Lead complex, cross-functional initiatives that span multiple teams, platforms, and business processes. • Integrate AI solutions with internal systems, APIs, databases, and development tools. • Own initiatives end-to-end - from problem discovery and architecture to hands-on implementation, deployment, and adoption. • Build reusable AI capabilities and infrastructure that scale across the organization. • Challenge existing processes, drive innovation, and deliver measurable improvements in efficiency and productivity. What We're Looking For • 5+ years of software engineering experience, including building complex, production-grade systems. • 2+ years of hands-on experience building AI-powered applications, agents, and automation workflows. • Exceptional systems thinking - the ability to understand complex processes, connect the dots, and see the bigger picture. • Strong ownership and independence - capable of turning ambiguous, cross-organizational challenges into working solutions. • Strong proficiency in Node.js / TypeScript and backend system architecture. • Deep experience with agentic AI, including tool calling, orchestration, context management, and multi-agent systems. • Familiarity with frameworks and protocols such as LangGraph, Google ADK, CrewAI, MCP, and AI evaluation and observability tools. • Hands-on experience with AI-native coding tools such as Claude Code, Cursor, or Codex. • Strong business and product mindset, with excellent communication skills and the ability to work across technical and non-technical teams. Why join us? • Real ownership from day one. Drive decisions, shape ideas and make them work. • Your fastest learning years. Build alongside founders and VPs in a space that moves weekly. • You'll have the opportunity to write and build what comes next.

Job Description You'll be a senior engineer on a deliberately flat, entrepreneurial team. Day to day you'll design and build agentic AI systems - agents, workflows, the orchestration layer that ties them together, and the infrastructure that makes all of it reliable at scale. This is hands-on building, not oversight. What you'll do • Design and build agentic workflows and the AI systems behind them - agents, the orchestration layer, and the infrastructure that runs them reliably • Take significant, ambiguous areas of the system and drive them from rough idea to working capability • Help scale the platform from a first working workflow to something used across the marketing organization • Contribute to evaluation, quality, and reliability - making sure systems don't just run, but run well • Work directly with the people who'll use what we build, and translate their needs into systems Qualifications • Substantial software engineering experience, with a track record of building and shipping complex systems • Hands-on experience building agentic or LLM-based systems - this is a requirement, not a nice-to-have. We’re looking for someone who has designed agent workflows, wrestled with prompts and context, handled the failure modes, and shipped something real • Strong product instincts: comfortable with ambiguity, able to define a problem before solving it, and opinionated about what's worth building • Comfort working in a small, flat, fast-moving team where you set much of your own direction • The ability to communicate clearly with non-technical partners across marketing Nice to have: • Experience with orchestration frameworks for agentic systems (e.g. LangGraph or similar) • Experience with evaluation frameworks, RAG, or working with knowledge bases at scale • Familiarity with the marketing domain, or a genuine interest in it • Experience taking a system from early prototype to broad organizational adoption Additional Information We're a small, fast-moving team building the AI systems that are changing how Wix's marketing organization works. Our goal is to take Wix marketing into the agentic era, where marketers are supported end-to-end by AI that carries real work from start to finish. This is a rare chance to build agentic AI that's actually in production and actually changing how a large organization works. Not a demo and not a proof of concept. You'll have real ownership, work alongside experienced engineers on genuinely hard problems, and help define what an AI-native marketing organization looks like. For more Information feel free to talk to Sasha Belenky.

Job Description As an AI Engineer, you'll work on cutting-edge technologies, tackle challenging technical problems, and influence the engineering culture at Base44. You'll become an industry leader in AI-native development while improving your skills and collaborating with top-notch engineers. You'll be part of a team that lives and breathes AI, redefining how software is built from the ground up. In your day-to-day, you will: • Work on cutting-edge technologies and become an industry leader • Use AI to bridge ideation to production in record time without compromising on code quality, security, or architecture. • Improve your skills and learn from top-notch engineers • Tackle tough problems and find creative ways to solve them • Push your code to millions of users every day • Solve tough technical challenges on a cutting-edge, AI-powered platform • Influence our engineering culture by contributing to internal knowledge sharing and, if you're interested, the open-source community Qualifications • 7+ years of software engineering experience in tech-first product companies or high-growth startups • AI-pilled daily workflow: You use AI coding tools as your primary workspace, leveraging AI across the full software lifecycle (planning/design, implementation, testing, refactoring, maintenance) while maintaining high standards for architecture, quality, security, scalability, and reliability • Hands-on with agents in production: tool calling, context management, evals, and cost and latency tradeoffs. Additional Information We’re Base44, a newly acquired part of Wix, on a mission to change how products and apps get built. Our AI-powered platform allows anyone to create custom applications using natural language—no traditional coding required. We operate like a startup within Wix: fast-moving, collaborative, and focused on solving complex problems with simple, elegant solutions. We’re here for anyone who wants to build: creators, solo founders, startups, entrepreneurs, side hustlers, and everyone in between. Whether you're launching a product, validating a concept, or chasing a hunch, Base44 gives you the power to make it real.

Description About Us We are an NVIDIA partner, delivering professional services in advanced software development, artificial intelligence systems, and high-performance AI solutions. We build production-grade AI systems optimized for NVIDIA GPU platforms, working across multiple applied AI domains, including Generative AI / Agentic Systems. Role Overview We are looking for an experienced AI Software Engineer to take a leading role in designing, building, and delivering advanced AI systems for real-world applications. This role is suited for a hands-on engineer with strong software engineering skills and deep experience in applied AI, who enjoys solving complex problems, owning technical solutions end-to-end, and mentoring junior team members. Projects typically focus on LLM or Multimodal LLM based agentic systems. What We Work On Our work spans software engineering and AI domains: • Design and implementation of agentic systems powered by Large Language Models (LLMs) • Deployment of open-source LLMs on NVIDIA GPUs • High-performance inference using NVIDIA technologies such as NVIDIA NIM (Inference Microservices) • System-level design for reliability, scalability, and performance • Multimodal agents for text, image, audio, and video processing • Performance optimization on GPU platforms Key Responsibilities • Lead the design and development of LLM-based agentic systems. • Own end-to-end delivery of AI solutions, from architecture and prototyping to production deployment using rigorous software engineering practices • Optimize model performance, latency, and throughput on NVIDIA GPU platforms • Design clean, maintainable, and scalable software architectures • Collaborate with customers, product teams, and engineers to translate requirements into technical solutions • Mentor junior engineers and contribute to technical best practices • Evaluate new tools, AI models, and frameworks and drive their adoption when appropriate Requirements • BSc or MSc in Computer Science, Electrical Engineering, or a related field • 4+ years of experience in software engineering and applied AI (or equivalent) • Strong knowledge of software design and development practices • Strong proficiency in Python and modern AI frameworks • Proven experience delivering production-grade AI systems • Solid understanding of deep learning architectures (CNNs, transformers) • Experience with system-level design, debugging, and performance optimization • Experience working with Large Language Models (LLMs) • Building agentic workflows, reasoning systems, or AI-driven applications • Deploying and optimizing open-source LLMs for inference Nice to Have • Experience with NVIDIA technologies (CUDA, TensorRT, Triton, NVIDIA NIM) • Experience with GPU performance profiling and optimization • Background in high-performance or low-latency systems • Experience with Multimodal LLM agents for text, image, audio, and video processing • Experience with React, TypeScript, Redis Pub/Sub, SQL, Containerized Development • Experience with Test-Driven Development, Agile Scrum methodology, Git workflows • Experience mentoring engineers or leading technical initiatives What We Offer • Ownership of complex, high-impact AI projects • Work with cutting-edge NVIDIA GPU and AI technologies • Influence over architecture, tooling, and technical direction • A collaborative, engineering-driven culture • Opportunities for technical leadership and professional growth • Real-world, production-scale AI challenges Full time Job Location: Haifa, Hybrid We at Deloitte believe that diversity and inclusion among our people is a critical component of our success and that is why we cultivate an organizational culture that contains and embraces diversity in all its forms.

Description We are seeking a talented Software Development Leader with a strong background in Large Language Models (LLM) and GenAI engineering. This is a unique opportunity to work with Deloitte US clients and engage in global projects, leveraging your extensive skills in generative AI tools. As a pivotal member of our team, you will be responsible for translating complex business problems into data-driven solutions, drafting methodologies, and executing innovative projects. In This Role You Will • Lead development of robust, efficient, and scalable Python code, ensuring adherence to best practices in software engineering and optimization for high-performance applications. • Utilize GenAI engineering tools such as LangChain, RAG, Agents, and Vector Database for implementation and optimization. • Stay updated with AI protocols and standards and ensure their correct application in projects. • Collaborate with other teams and team members to understand requirements and develop solutions. • Analyze complex problems, identify and define the computational requirements to solve them. Requirements • Minimum of 8 years of experience as a Back End developer. • Deep knowledge of Generative AI principles, including Large Language Models (LLMs) and RAG techniques and, modern deployment architectures. • Ability to lead team to design services, modules, APIs, and folder structures that enable REST API communication and facilitate a plug-and-play approach for various agent pods (compatible with langgraph, pydanticAI, etc.). • Practical Implementation: Hands-on experience in implementing and integrating new ideas and tools within the GenAI landscape. • Programming and Tools: Proficiency with Python, PySpark, Langchain, LlamaIndex, RAG, ChromaDB, QDrant, Weaviate, Neo4j, Knowledge Graphs, AWS Bedrock, GCP Vertex, Azure OpenAI, Git/GitHub, Docker, SQL, FastAPI, PyTorch/TensorFlow, and Pydantic. • Cloud Platforms: Experience with managed cloud services provided by hyperscalers such as AWS, Azure, or GCP. • Excellent problem-solving and analytical skills. • Degree in Computer Science, Artificial Intelligence, Machine Learning or a related field. • Advanced level of English. • Working Israeli permit – a must. Advantage • B.A/M.Sc. in Data Science, Computer Science, Mathematics, Statistics, etc. – an advantage. Full time Job Location: Tel Aviv, Hybrid We at Deloitte believe that diversity and inclusion among our people is a critical component of our success and that is why we cultivate an organizational culture that contains and embraces diversity in all its forms. Requirements Hebrew .

Description We are seeking a talented AI engineer with a background in Large Language Models (LLM) and GenAI engineering. The ideal candidate will have professional experience programming in Python and a solid understanding of AI protocols and standards. In this role, you will: • Implement effective and scalable Python code. • Develop and implement GenAI applications, including Large Language Models (LLM). • Utilize GenAI engineering tools such as LangChain, RAG, and Vector Database for implementation and optimization. • Stay updated with AI protocols and standards, ensuring their correct application in projects. • Collaborate with other team members to understand requirements and develop solutions. • Analyze complex problems, identifying and defining the computational requirements to solve them. Requirements • Minimum of 5 years of experience as an AI engineer/developer • Professional programming experience in Python • Knowledge of backend frameworks such as Node.js and Django • Familiarity with APIs such as JSON and REST • Experience with GenAI engineering, implementation, and tools (e.g., LangChain, RAG, Vector Database) • Good understanding of AI protocols and standards • Frontend development experience in React or Angular is an advantage • Degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field • Excellent problem-solving and analytical skills • Experience working on global teams and collaborating via tools such as Jira, Teams, and Azure DevOps (ADO) • Advanced level of English • Valid Israeli work permit – mandatory • B.A./M.Sc. in Data Science, Computer Science, Mathematics, Statistics, etc. – an advantage Full time Job Location: Tel Aviv, Hybrid We at Deloitte believe that diversity and inclusion among our people is a critical component of our success and that is why we cultivate an organizational culture that contains and embraces diversity in all its forms.

Description VAST Data is looking for a Senior AI Engineer to design and build production-grade, LLM-powered systems. You'll work at the intersection of software engineering and applied AI — shipping agents, RAG pipelines, and tool-using systems that solve real problems at scale. This is a hands-on, high-ownership role for someone who thrives at the frontier of what's possible with modern LLMs and isn't afraid to write the glue, the infrastructure, and the prompts that make it all work. This is a **cross-functional, company-wide role**. You won't be embedded in a single product team — instead, you'll partner with every department to identify high-leverage opportunities and build AI-powered tools and workflows that boost productivity and efficiency across the entire organization. This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence. "VAST's data management vision is the future of the market."- Forbes VAST Data is the data platform company for the AI era. We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and inference. Designed from the ground up to make AI simple to deploy and manage, VAST takes the cost and complexity out of deploying enterprise and AI infrastructure across data center, edge, and cloud. Our success has been built through intense innovation, a customer-first mentality and a team of fearless VASTronauts who leverage their skills & experiences to make real market impact. This is an opportunity to be a key contributor at a pivotal time in our company’s growth and at a pivotal point in computing history. What You'll Do: - Design, build, and operate LLM-powered applications, agents, and workflows end-to-end — from prototype to production. - Architect retrieval, context engineering, and tool-use strategies that make models reliable, accurate, and cost-efficient. - Integrate LLMs with internal services, third-party APIs, and data stores to automate complex business and engineering workflows. - Build, evaluate, and continuously improve evaluation harnesses for non-deterministic systems. - Collaborate closely with product, research, and platform teams to translate ambiguous problems into shipped capabilities. - Stay ahead of the rapidly evolving LLM ecosystem (models, frameworks, agentic patterns) and bring the best ideas into our stack. Requirements Engineering Foundations: - Strong Python skills- you write clean, idiomatic, well-tested code and understand the language deeply. - Hands-on experience using coding agents(Cursor, Claude Code, GitHub Copilot, or similar) to build complex software systems. You know how to delegate effectively to AI assistants and review their output critically. - Experience with multiple database paradigms- both SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis, DynamoDB, or similar). You can choose the right tool for the job. - Experience designing and integrating with third-party APIs- REST and gRPC. Comfortable building robust clients, handling auth, retries, rate limits, and schema evolution. - Production experience with Docker and Kubernetes- containerizing services, writing manifests, and debugging deployments. - Strong Linux fundamentals- confident in bash and the terminal; you can navigate, script, and troubleshoot a server without reaching for a GUI. - Experience building cloud-native tools on AWS, GCP, or Azure (compute, storage, queues, serverless, IAM). AI / LLM Expertise: - Solid understanding of what an LLM is and how it works- tokenization, attention, context windows, sampling, and the practical implications of each for system design. - Strong grasp of modern patterns for integrating LLMs into real workflows, including RAG, MCP (Model Context Protocol), vector databases, agents, tool use, and context engineering- with hands-on experience building with several of them. - Production experience implementing LLM-powered systems end-to-end, using relevant tools and frameworks (e.g. LangChain, LlamaIndex, LangGraph, Haystack, Pydantic AI, vector stores like Pinecone/Weaviate/pgvector, observability tools like LangSmith or Langfuse). - Solid foundation in core ML concepts; embeddings, evaluation, overfitting, generalization, and how classical ML relates to and differs from modern LLM-based approaches. Nice to Have: - Experience fine-tuning or distilling open-source models. - Contributions to open-source AI/ML projects. - Experience with streaming, real-time systems, or low-latency inference. - Familiarity with prompt evaluation frameworks and LLM-as-judge methodologies. - Background in distributed systems or high-scale backend engineering. What We Look For: - A builder's mindset; you ship, measure, iterate, and don't get stuck in analysis. - Comfort with ambiguity; LLM systems are non-deterministic and the field moves weekly. You navigate that with curiosity rather than frustration. - Strong communication; you can explain trade-offs to engineers, product managers, and executives alike. - Pragmatism; you know when to reach for a 200-line script and when to invest in proper infrastructure.