AI Engineer jobs in Tel Aviv-Yafo

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.

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.

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 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.

Description #Hybrid DriveNets builds high-performance networking solutions for large-scale AI infrastructure and service-provider networks. DriveNets’ Network Cloud powers production networks at global operators such as AT&T and Comcast, while its AI Fabric solutions optimize the performance and time to first token (TTFT) in multi-vendor AI environments at foundation model labs, NeoClouds, and enterprises. DriveNets combines high-performance networking, end-to-end automation, and full-stack AI cluster optimization to remove network bottlenecks, maximize GPU utilization, accelerate AI cluster deployments, and improve token economics Job Summary We are looking for a talented and motivated Software Engineer with hands-on experience building and operating multi-agent AI systems in production to join our DriveNets Automation Platform (DAP) team. The team develops automation tools, orchestration capabilities, and intelligent platforms that simplify the deployment, management, troubleshooting, and optimization of large-scale network and AI infrastructure environments. You will work on the design and development of AI-powered systems that bridge networking, automation, observability, and distributed infrastructure — running on Kubernetes at scale. Our stack includes LangGraph, Langfuse, RAG pipelines, MCP, and agent-to-agent (A2A) communication patterns. This role combines strong software engineering with practical AI application development, with a sharp focus on production hardening, tracing, evaluation, and safety of agentic systems — not model training or research prototypes. Requirements • 8+ years of hands-on software engineering experience building production-grade backend services, APIs, or AI-powered systems. • Proven production experience with multi-agent AI systems: deployment, tracing, guardrails, hardening, and incident management. • Hands-on experience with agentic frameworks such as LangGraph, CrewAI, Google ADK, AutoGen, or equivalent. • Experience building and running evaluation pipelines for agentic solutions - including trajectory tracing, ground truth validation, and harshness/quality scoring. • Strong Python proficiency: comfortable building scalable backend services using gRPC and REST APIs. • Solid understanding of distributed systems: fault tolerance, consistency models, service communication, and operational challenges at scale. • Hands-on Kubernetes experience: deploying and operating containerized services, managing workloads, config, and scaling in production clusters. • Practical experience with embeddings, vector databases, and semantic retrieval systems in production. • Practical experience with RAG pipelines, LLM API integration, structured outputs, and tool calling in production environments including building and serving MCP servers at scale. • Working knowledge of SQL and/or NoSQL databases, schema design, and query optimization. • Strong debugging skills across application logic, APIs, data, and AI agent behavior. • Strong communication skills and a bias toward ownership and delivery. Nice to Have • Familiarity with Langfuse/Arize Pheonix. • Familarity with A2A & A2UI protocols. • Experience with network automation, orchestration, or configuration management (Ansible, Terraform, NETCONF, gNMI, or similar). DriveNets is on a mission to build a special company comprised of individuals with diverse backgrounds, perspectives, and experiences. DriveNets is an equal opportunity employer. We do not discriminate based on upon race, religion, national origin, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with disability, or other applicable legally protected characteristics.

NVIDIA is at the forefront of the AI revolution, delivering brand new accelerated compute platforms for global impact. Our Network Architecture group is seeking a talented and motivated Sr. Software Engineer to build the agentic workflows that our architects use in their daily work. The software at the center of this role is our hardware network simulation environment — you will design multi-step agent workflows over it, engineer the context that grounds them in our own specifications and source code, and optimize their runtime performance. If you are passionate about building the practical infrastructure that brings intelligent agents to life, we want to hear from you. What you'll be doing: • Build agentic workflows — loops, graphs, and multi-step pipelines — that carry real hardware network simulation and analysis work end to end. • Engineer the context these workflows run on, turning our simulation models, specifications, design documents, and source code into context that makes agents accurate in our domain. • Work closely with network architects to understand their workflows and translate them into agent workflows they use daily. • Optimize the runtime performance of our simulation tooling on these platforms, including execution time, compute cost, and end-to-end latency. • Define evaluation and regression testing for agent workflows, so that changes to a prompt, a graph, or a context source are measurable. • Build observability across agent runs: what the agent did, where it failed, and why. • Champion guidelines for secure and reliable agent workflows, including data handling, access control, and interaction boundaries. • Serve as a key technical resource for solving sophisticated integration issues between agents and internal tooling. What we need to see: • B.Sc. or above in Computer Science, Computer Engineering, or a related field, or equivalent experience. • 5+ years of hands-on experience in software engineering, with demonstrated ownership of production systems from design through deployment. • Expert-level programming skills in C++, with strong Python skills alongside it. • Strong understanding of the full stack, including hardware: memory, I/O, networking, accelerators, and where real performance bottlenecks occur. • Current, practical knowledge of how to build systems around AI models: agent loops, tool interfaces, context retrieval and management, and common failure modes. • Understanding of inference serving, including request lifecycle, batching, caching, and the tradeoffs between throughput, latency, and cost. Ways to stand out from the crowd: • Experience writing hardware simulation software — network, system, or architectural simulators, models, or testbenches. • Networking experience — protocols, fabrics, switching, or RDMA — and experience working alongside silicon, systems, or architecture teams. • Hands-on experience with inference serving engines such as vLLM, TensorRT-LLM, or Triton Inference Server, including low-level internals such as KV cache, batching and scheduling, and quantization, and related performance work such as profiling and GPU programming. • Hands-on experience building or fine-tuning LLMs or other generative models. • Agent workflows, tooling, or context pipelines adopted by other engineering teams. NVIDIA is home to some of the most innovative and dedicated professionals in the industry. We are committed to fostering a diverse work environment and are proud to be an equal-opportunity employer.

Cato Networks is the converged network and security cloud for the AI era. As AI reshapes cybersecurity, enterprises face a dual challenge: unlocking AI’s potential while defending against AI-driven attacks. Cato addresses both through a unified, cloud-native platform, providing the visibility and context to prioritize risks and stop threats in real time across users, applications, data, and AI agents. Join us as we scale: take on ambitious technological challenges and shape the next generation of enterprise security at a company trusted by thousands of organizations worldwide. We're looking for a hands-on Agentic AI Engineer to build practical, high-impact AI solutions for our Product Support organization. This is not a research role. You'll design and ship real AI systems that improve support workflows and processes - building custom solutions where off-the-shelf tools fall short. The role also requires close collaboration across teams: aligning with different stakeholders' needs and priorities, and building strong, ongoing partnerships across the organization. Responsibilities: • Partner directly with business teams to identify automation and optimization opportunities • Design and implement agent-based AI workflows to automate internal processes end-to-end • Design and build LLM-powered tools (agents, workflows, copilots) using frameworks like LangGraph / LangChain • Develop RAG pipelines, integrate multiple data sources, and build intelligent automation flows • Deep-dive into company data - validate quality, uncover gaps, and ensure AI solutions are built on solid foundations • Take solutions from idea → prototype → production • Governance, Reliability & Security • Ensure AI workflows comply with security, privacy, and compliance requirements • Implement guardrails, approvals, logging, and human-in-the-loop mechanisms where needed • Monitor AI performance, errors, hallucinations, and drift • Collaboration & Enablement: • Partner with business owners to identify automation opportunities • Translate business requirements into AI-driven solutions • Document AI flows, decision logic, and operational runbooks • Educate internal teams on AI capabilities and limitations Requirements: • 3 years of hands-on software development experience, including writing, maintaining, and delivering production-quality code • 2+ years of GenAI development experience, with strong AI/ML focus - MUST • Strong Python skills and production mindset - MUST • Hands-on and deep understanding with LLMs, SLMs, prompt engineering, context engineering and agent-based systems • Experience with LangGraph, crewAI, Strands or similar orchestration frameworks • Experience in enterprise grade agentic solutions and bringing Agents into production • Experience in AWS Agent Core - Advantage • Solid understanding of ML workflows and MLOps principles • Strong analytical skills and ability to work directly with non-technical stakeholders • Builder mindset: proactive, independent, and impact-driven • Experience with Agentic AI driven applications like n8n, UiPath, Make –Advantage • Experience or familiarity with the Support domain – Advantage

Cato Networks is the converged network and security cloud for the AI era. As AI reshapes cybersecurity, enterprises face a dual challenge: unlocking AI’s potential while defending against AI-driven attacks. Cato addresses both through a unified, cloud-native platform, providing the visibility and context to prioritize risks and stop threats in real time across users, applications, data, and AI agents. Join us as we scale: take on ambitious technological challenges and shape the next generation of enterprise security at a company trusted by thousands of organizations worldwide. Cato is building a real-time AI runtime platform for security algorithms running inline across our global cloud and physical PoPs. We are looking for a hands-on AI Platform Team Lead to build and lead the team behind this platform: a high-throughput, low-latency engine that runs GPU-based models, from MMBERT-style models to LLMs, together with CPU-based heuristics and security logic. This is a core infrastructure role for someone who wants to own the runtime layer of AI security at scale: performance, reliability, orchestration, GPU efficiency, and production-grade execution in the traffic path. The team will also own the model lifecycle required to take AI security algorithms from research to large-scale production, working closely with research and algorithm teams. Responsibilities • Build and lead Cato’s AI Platform team: hiring, mentoring, architecture, technical direction, and execution. • Own the AI security runtime platform for high-throughput, low-latency inline security decisions across Cato’s global cloud and PoPs. • Design the orchestration layer for running GPU models, CPU heuristics, and security logic as one production engine. • Own production readiness: observability, SLOs, autoscaling, reliability, rollout, rollback, and operational health. • Own the model lifecycle platform: registry, versioning, deployment, monitoring, and safe production rollout. • Work closely with research and algorithm teams to productionize AI security models and algorithms at scale. • Define the long-term platform strategy for AI runtime and model serving at Cato. Requirements • 3+ years of leadership experience as a team lead, tech lead, or engineering manager. • 3+ years of hands-on experience in AI inference, production ML infrastructure, model serving, or AI runtime platforms. • Strong experience with production inference technologies such as Triton, vLLM, CUDA, Kubernetes, Docker, PyTorch, ONNX, TensorRT, or similar. • 3+ years of experience with Go, or strong experience with a similar high-performance backend language such as C++, Rust, or Java. • Experience with performance optimization, scalability, observability, and SLO-driven production ownership. • Strong system design skills, especially around distributed systems, performance, reliability, and production infrastructure. Advantages Experience with GPU optimization, GPU scheduling, GPU resource efficiency, quantization, runtime acceleration, or large-scale model serving.

About monday.com monday.com is the AI work platform powering the most ambitious teams. 250,000+ customers across departments use us to bring people, workflows, and AI agents together on one flexible platform where AI doesn't just assist, it executes. We move fast, build things that matter, and foster an ownership-driven culture where you're empowered to shape how organizations work and outpace their competition. About the Team RevAI is the team building the AI agents inside monday.com's revenue organization, as part of BigBrain, monday.com's internal data and AI group. Our mission is to reinvent how monday.com's Sales and Customer Success organizations work, making them truly agentic end to end, from the first touch with a lead all the way to closing the deal and supporting customers. Our agents book meetings, run outbound, handle inbound leads, and help sales reps manage their accounts with AI-generated account plans, next-best actions and ready-to-send drafts that write straight back to the CRM. We work closely with the business: sales, RevOps and GTM leadership. That means we understand the business process first, then turn it into agents running in production. Our agents run on an agentic platform we built in-house. It is event-driven and operates across hundreds of thousands of accounts, so LLM cost, latency, reliability and business impact are everyday problems for us. We're a small team with high ownership and low ego, and we prefer to just try things rather than wait for permission. About the Role Lead a team of AI software engineers: mentor and grow them, set priorities, and own delivery from planning to production Design, code and ship AI agents and agentic systems alongside the team Work closely with the business, partnering directly with sales, RevOps and GTM stakeholders to understand revenue processes, find high-impact opportunities, and turn business needs into agents with measurable outcomes Own the technical direction of our in-house agent platform and the agents running on it: architecture and design docs, event processing and orchestration, policies and guardrails, human-in-the-loop flows, and tool integrations Integrate LLMs in production through an AI gateway, and tune model routing, prompt caching, token budgets and rate limits for scale, cost and quality Build and harden integrations with CRM and GTM systems (e.g. Salesforce, email, voice and messaging providers, scheduling tools) Set the bar for engineering quality and reliability, including code reviews, monitoring and alerting, incident response, and resilient long-running workflows Manage expectations and communicate progress, trade-offs and impact to stakeholders and leadership Requirements 5+ years of software engineering experience in the industry, shipping production systems Experience leading or mentoring engineers, either as a team lead or as a strong tech lead who is ready to step into management Strong server-side expertise in TypeScript/Node.js (or similar), with experience building microservices, APIs and distributed or event-driven systems at scale Proven experience shipping LLM-powered features or AI agents to production (prompting, tool calling, evaluation, cost/latency trade-offs) Previous experience building agents and workflows with frameworks and tools such as LangChain/LangGraph, n8n or similar Strong business acumen and comfort with revenue/GTM processes (lead management, sales pipeline, account management), with the ability to translate business problems into technical solutions Proven stakeholder management, working directly with non-technical partners and aligning priorities across teams Strong ownership and observability mindset, and comfort debugging production issues end to end Excellent communication skills, team mindset, and a bias for action Nice to Have Experience with Salesforce or other CRM/GTM platform integrations Background in sales engineering, solutions engineering, or other customer-facing technical roles Familiarity with agent frameworks and patterns (multi-agent orchestration, memory, evaluation, guardrails) Experience with React and micro-frontend architectures Experience with Kubernetes, AWS and CI/CD Experience with data pipelines and workflow tools (e.g. Airflow, Python, Snowflake) Background in voice or conversational AI If this sounds like your kind of challenge, we're looking for an AI Software Engineer Team Lead to build and lead the team shaping how AI agents drive revenue at monday.com. We believe in equal opportunity. At monday.com, we believe everyone should feel they belong - exactly as they are. We're an equal opportunity employer, committed to an open, accessible, and inclusive workplace free from discrimination or harassment of any kind. All qualified candidates will be considered for employment, regardless of race, color, religion, nationality, sexual orientation, gender identity, age, marital status, pregnancy, family or parental status, disability, veteran status, or any other characteristic protected by law. If you need support or accommodation during the hiring process, we're here to help. Meet the R&D team The R&D Team is passionate about building innovative and lovable products, while tackling complex engineering problems at a great scale. We're accountable for bringing the company's vision to life by navigating our progress into flawless execution and encouraging full ownership and independence in all projects.

Meet render.ai, monday.com's new AI venture. At render.ai, we're redefining how humans use AI for work. render.ai enables anyone to bring ideas to life in minutes, using their words. We're a small, autonomous team - closer in spirit to an early-stage startup than to an established company. There's no fixed playbook: we're still figuring out what the product looks like, and every engineer helps shape that, not just build it. What are we looking for? You love prompt engineering for LLM and image generation, chasing high-fidelity outputs at scale, and you know how to push foundation models further than most think possible. You own the model quality lifecycle end-to-end, from early experiments to production monitoring, turning the latest LLM breakthroughs into systems that hold up at scale. You build evaluation frameworks you can trust, offline tests, and A/B experiments that turn feedback into real, measurable improvements. You keep a close eye on live AI systems, watching latency, hallucinations, and drift, and get ahead of failure modes before they become real problems. You're genuinely strong in TypeScript and Python, comfortable moving between fast AI experimentation and solid production engineering. You like getting hands-on with data, sourcing and cleaning it to make prompts, models, and evals better. You're energized by ambiguity and fast-moving environments, always curious about the newest models and techniques on the frontier. You're excited about where this goes next, helping render.ai expand into new modalities like voice and video. Advantages: Experience with modern LLMs and image models such as Flux and Imagen. Experience building AI-native or agent-based products from scratch. Familiarity with LLM observability tools, tracing, and debugging workflows. Background in rapid prototyping, experimentation, or startup-like environments.

At JFrog, we’re reinventing DevSecOps to help the world’s greatest companies innovate. Our team of industry-leading software security experts are true pioneers, constantly pushing the boundaries with original research and technological innovation. JFrog is a special place with a unique combination of brilliance, spirit and just all-around great people. Thousands of customers, including the majority of the Fortune 100, trust JFrog to manage, accelerate, and secure their software delivery from code to production – a concept we call “liquid software”. Wouldn't it be amazing if you could join us on our journey? We are looking for an AI Fullstack Engineer to join our Competitive Intelligence team. This role combines deep technical expertise with a builder's mindset to design, implement, and maintain advanced AI-powered systems for automating knowledge collection, generating competitive insights, and ensuring broad internal knowledge sharing across the organization. You will spearhead AI solution projects from initial concept through execution and widespread adoption. As an AI Fullstack Engineer - Competitive Intelligence at JFrog, you will… • Define architectural approaches and detailed technical engineering specifications. • Main role: Build, implement, and maintain the AI-powered intelligence stack, using LLMs, agentic capabilities, MCPs, Skills, and advanced RAG, to automate data collection, analysis and sharing • Make knowledge impossible to miss inside JFrog. Build the competitive intel team’s interfaces that get the right competitive insight to the right stakeholder at the right time • Drive projects from concept to execution to delivery • Evaluate and recommend ML and AI tools and frameworks to enhance productivity and effectiveness • Ensure the scalability and reliability of LLM-based system architectures • Engage with requirement gathering and product discussions with internal customers at JFrog • Be the focal point for collaborating with IS, IT and data science teams • Have solid understanding of various aspects of the software development supply chain, including DevOps, DevSecOps and MLOps, and conduct in-depth technical research around them To be an AI Fullstack Engineer - Competitive Intelligence at JFrog you need… • A proactive builder's mindset: a desire to automate workflows, take end-to-end ownership, and drive continuous improvement • Bachelor's degree or higher in Computer Science, Data Science, Software Engineering, or similar • 4+ years of relevant hands-on experience in developing and scaling production-grade GenAI architectures using modern LLM stacks • Proficiency with relevant tools, processes, and frameworks, such as: LangChain, CrewAI, OpenClaw, NLP, Vector databases, RAG, building MCPs and Skills • Coding fluency in Python and at least one other language (TypeScript/JavaScript, Go or Rust) • Deep understanding of cloud and cloud-native principles, including hands-on experience with major Cloud environments (AWS, GCP, Azure) and containers/Kubernetes • Proven ability to conduct deep technical investigations – analyze complex systems, cloud environments, source code, and documentation, and synthesize the collected data into clear insights • Passion and curiosity to stay current of industry trends and technological advancements • Great communication skills and proven ability to serve as a liaison, coordinating and driving action across diverse org-groups (IS, IT, data science) to ensure effective enterprise-wide systems integration • Excellent English communication (written and verbal) • Comfortable in a dynamic, fast-paced company Significant Advantages: • Full-stack web development experience • 3+ years of relevant hands-on experience in setting up, configuring, and using a broad range of industry DevSecOps technologies (ex. Kubernetes, JFrog Artifactory, GitLab, SonarQube, coding agents, security vulnerability scanners, GitHub Actions)

Who Connecteam is: Connecteam is a TLV-based startup that’s on a mission to change the work experience for 80% of the world’s global workforce - the deskless employees. Our business management platform helps thousands of businesses thrive by taking away the daily hustle and complexities of managing teams, so they can have the peace of mind to grow and run their business. About the Role: We’re looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users. This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features—from data pipelines and LLM orchestration to intuitive UI experiences—with a strong product mindset. Responsibilities: 🧠 AI Agent Design & Integration • Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models). • Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems. • Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents). 🏗 Fullstack Product Development • Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces. • Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance. • Collaborate closely with design, product, and data teams to bring ideas from concept to production. ⚙️ Systems & Infrastructure • Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability. • Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference. • Ensure systems are secure, reliable, and compliant with InfoSec standards. 🧪 Experimentation & Continuous Improvement • Rapidly prototype and iterate on new AI capabilities and user experiences. • Analyze performance and usage metrics to drive product and model improvements. • Stay up to date with the evolving AI toolchain and emerging agent architectures. Requirements: • 8+ years of fullstack development experience with strong skills in TypeScript/JavaScript, React, and Python (or Node/Go for backend). • Solid understanding of LLM APIs, agent frameworks (e.g., LangChain, AutoGPT, CrewAI), or custom AI pipelines- Advantage • Experience with modern cloud infrastructure (e.g., AWS, GCP, Docker, CI/CD). • Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG)- Advantage • Product-oriented mindset: you care deeply about building things that work well for users. • Bonus: experience with observability, feedback loops for AI agents, or embedded AI evaluation techniques. Why Join Us: • Shape the foundation of our AI-first product vision. • Work closely with a world-class team of engineers, product leaders, and data scientists. • Opportunity to own impactful systems and ship fast in a nimble environment. • Competitive compensation, equity, and benefits in a fast-growing company. • #LI-Hybrid Joining Connecteam Is The Smart Move: • We build our people up. Every team member is treated as a long-term investment and we recognize the value in always nurturing and training them so they can go above and beyond in their skills and job duties. • We make an impact on our customer’s business. We are on a mission to provide managers of all business types and sizes with the tools they need to communicate, operate, engage, and run their deskless workforce. Our product offers them an effective and affordable solution to run their business. • We get the job done. Connecteam employees are passionate in executing their job duties so they can drive the company forward and provide real value to our customers. • We have fun! From weekly happy hours to holiday parties, we always enjoy each other’s company (and good food, of course). Connecteam is like one big, happy family! • Everyone is welcome. Connecteam is committed to building an encouraging, caring, and supportive environment. We share a responsibility to support our team and enrich their lives. Together we will shape the future of work! Our privacy policy

Who Connecteam is: Connecteam is a TLV-based startup that’s on a mission to change the work experience for 80% of the world’s global workforce - the deskless employees. Our business management platform helps thousands of businesses thrive by taking away the daily hustle and complexities of managing teams, so they can have the peace of mind to grow and run their business. About the Role: We’re looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users. This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features—from data pipelines and LLM orchestration to intuitive UI experiences—with a strong product mindset. Responsibilities: 🧠 AI Agent Design & Integration • Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models). • Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems. • Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents). 🏗 Fullstack Product Development • Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces. • Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance. • Collaborate closely with design, product, and data teams to bring ideas from concept to production. ⚙️ Systems & Infrastructure • Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability. • Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference. • Ensure systems are secure, reliable, and compliant with InfoSec standards. 🧪 Experimentation & Continuous Improvement • Rapidly prototype and iterate on new AI capabilities and user experiences. • Analyze performance and usage metrics to drive product and model improvements. • Stay up to date with the evolving AI toolchain and emerging agent architectures. Requirements: • 8+ years of fullstack development experience with strong skills in TypeScript/JavaScript, React, and Python (or Node/Go for backend). • Solid understanding of LLM APIs, agent frameworks (e.g., LangChain, AutoGPT, CrewAI), or custom AI pipelines- Advantage • Experience with modern cloud infrastructure (e.g., AWS, GCP, Docker, CI/CD). • Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG)- Advantage • Product-oriented mindset: you care deeply about building things that work well for users. • Bonus: experience with observability, feedback loops for AI agents, or embedded AI evaluation techniques. Why Join Us: • Shape the foundation of our AI-first product vision. • Work closely with a world-class team of engineers, product leaders, and data scientists. • Opportunity to own impactful systems and ship fast in a nimble environment. • Competitive compensation, equity, and benefits in a fast-growing company. • #LI-Hybrid Joining Connecteam Is The Smart Move: • We build our people up. Every team member is treated as a long-term investment and we recognize the value in always nurturing and training them so they can go above and beyond in their skills and job duties. • We make an impact on our customer’s business. We are on a mission to provide managers of all business types and sizes with the tools they need to communicate, operate, engage, and run their deskless workforce. Our product offers them an effective and affordable solution to run their business. • We get the job done. Connecteam employees are passionate in executing their job duties so they can drive the company forward and provide real value to our customers. • We have fun! From weekly happy hours to holiday parties, we always enjoy each other’s company (and good food, of course). Connecteam is like one big, happy family! • Everyone is welcome. Connecteam is committed to building an encouraging, caring, and supportive environment. We share a responsibility to support our team and enrich their lives. Together we will shape the future of work! Our privacy policy

Description A winning ad could change the trajectory of a mobile game. The only way to consistently find winners is to explore more, faster, and smarter than anyone else. Sett is a UA creative performance platform for mobile gaming. We build agentic AI systems that analyze performance data, generate diverse playable and video ad concepts, deploy them to ad networks, and continuously learn from the results. The full creative loop. Automated, and done better than humans only. Our system doesn't remix templates. It creates fundamentally different creative hypotheses, each one built from real performance signals. Sett is looking for a Senior AI Software Engineer to join our out-of-this-world, cross-functional team. If you’re someone who loves taking ownership, enjoys working across the stack, and isn’t afraid to dive into new technologies - this might be your perfect role. Responsibilities • Own end-to-end feature development - from design and coding to testing and production • Work on LLM based applications including the development of proprietary AI agents • Collaborate with team members through design/code reviews and open discussions • Partner closely with research and engineering to deliver impactful solutions Requirements • At least 8 years of experience in software development - a MUST • Strong hands-on experience with Python (at least 4 years) • Minimum 2 years of experience as an ML Engineer, Data Scientist, or in a similar AI-focused role - a MUST • Proven ability to develop and maintain complex backend systems • Curiosity, drive, and a passion for building great tech