AI Engineer jobs in Tel Aviv-Yafo

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. You'll build products where AI isn't a feature - it's the product. From customer-facing experiences to the multi-agent systems behind them, you'll own problems end-to-end, ship continuously, and help define how people work with AI. Responsibilities • Build customer-facing AI products from idea to production. • Design and build AI agents that solve real customer problems. • Create and improve agentic workflows using LangGraph, LangChain, and the Claude Agent SDK. • Build the orchestration layer that lets multiple AI agents collaborate, reason and complete complex tasks. • Own features end-to-end, from React UI to Python backend. • Design APIs and distributed services powering our agentic platform. • Improve reliability, observability and performance across production AI systems. • Work closely with Product, Design and AI Engineers to ship continuously. Requirements • You have 6+ years of experience building web products with Python, React, and TypeScript. • You know how to design clean APIs and scalable architectures. • You have experience with AWS, Docker, Kubernetes, and microservices. • You care about reliability, observability, and production quality (logs, metrics, tracing, and monitoring). • You have built or worked on production AI applications using tools like LangGraph, LangChain, the Claude Agent SDK, or similar frameworks. • You like shipping fast, owning problems end-to-end, and working across the entire stack. • You enjoy solving ambiguous problems and turning ideas into production software

About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role We’re looking for a Principal AI Software Engineer to lead the design and development of the evolution and scaling of Aidoc’s AI architecture. You’ll combine hands-on development with architectural leadership - solving complex engineering challenges, guiding your team through design decisions, and ensuring our systems are robust, scalable, and maintainable. You’ll collaborate with other senior engineers, tech leads, and product partners to define technical direction, drive innovation, and improve engineering practices across the teams and groups. This is a role for someone who thrives on building well-designed systems, driving technical excellence within the team and mentoring peers. Responsibilities • Lead the design and implementation of scalable and reliable backend services. • Drive architectural discussions and make key technical decisions within your domain. • Collaborate with algo teams and cross-functional teams to translate business and product goals into technical solutions. • Deliver high-quality, maintainable, and testable code while ensuring best practices for security, performance, and reliability. • Mentor and support engineers through design reviews, code reviews, and knowledge sharing. • Continuously improve development processes, observability, and deployment pipelines. • Contribute to the evolution of the platform’s architecture as the company and product scale. Requirements • BA/BSc/MSc in Computer Science, Engineering or a related field. • 10+ years of hands-on experience designing and developing complex, production-grade systems. • Proven track record in architecting and leading large-scale software projects. • Deep understanding of system design, distributed systems, and software architecture patterns. • Strong coding skills in one or more modern backend languages (e.g., Python, Go, Node.js, Java, C#). • Experience with cloud environments (AWS or equivalent), containerized deployments, and infrastructure as code (e.g., Docker, Kubernetes, Terraform). • Experience designing and scaling event-driven architectures and data-intensive systems. • Excellent communication and influencing skills - able to align multiple teams toward a shared technical vision. • A proactive mindset, strong sense of ownership, and passion for solving complex engineering problems. • Advantage: Experience in developing AI and machine learning solutions, with a focus on computer vision and NLP. Working at Aidoc Our Perks: • Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) • We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. • Amazing and healthy breakfasts and lunches prepared daily by our personal chef! • Stocked up kitchen & meal card • Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. • Amazing culture - collaborative, transparent & fun! • Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role This is a leadership role within Aidoc’s core AI group, focused on building and evolving the AI-facing software systems that enable our algorithms to move from research into robust, production-ready components. The AI Software team is responsible for developing the software layers, tooling, and core systems that support the development, execution, and operational readiness of AI models throughout their lifecycle. As a Team Lead, you will shape the team’s technical direction, guide execution, and remain deeply hands-on, contributing to architecture, implementation, and key technical decisions. You will lead a scrum team, work closely with AI researchers and algorithm engineers, and collaborate with product and engineering partners. The role combines strong software engineering with AI context, in a culture where software quality is a core enabler of AI excellence, and technical leadership is grounded in ownership, clarity, and impact. Responsibilities • Lead the team’s work on core software systems that sit at the intersection of algorithms and engineering, owning their design and implementation as part of the overall solution. • Guide and support team members’ growth, providing technical leadership, mentoring, and day-to-day coaching while fostering ownership and accountability. • Stay deeply hands-on in design and implementation, contributing code and solving complex software engineering problems where impact is highest. • Collaborate closely across teams, working with algorithm engineers, Product, and Engineering partners to define interfaces and align priorities. • Own project-level architecture and technical decisions, ensuring high-quality systems through sound design, code reviews, testing practices, and clear documentation. Requirements • BSc or MSc in Computer Science, Engineering, or a related field. • At least 7 years of hands-on experience building complex software systems. • At least 3 years of experience as a team leader, actively contributing to design and code development. • Experience designing and building core software systems that are an integral part of algorithmic and AI-driven solutions. • Deep understanding of computer science fundamentals, including object-oriented design, performance optimization, and system complexity. • Strong ability to lead end-to-end development processes while remaining technically involved. • Strong communication and collaboration skills, with the ability to work effectively across teams. • A strong sense of ownership and accountability, leading by example and driving execution. • A collaborative leader who listens, values others’ input, and motivates team members. • Strong commitment to clean code, sound architecture, and high engineering standards. Working at Aidoc Our Perks: • Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) • We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. • Amazing and healthy breakfasts and lunches prepared daily by our personal chef! • Stocked up kitchen & meal card • Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. • Amazing culture - collaborative, transparent & fun! • Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

About Aidoc Aidoc is the market leader in healthcare AI and has developed the world's largest clinical frontier model, supporting nearly 50 million patients each year. Aidoc is deployed in more than 2,000 medical centers worldwide. Since our founding in 2016, Aidoc has raised over $500 million and achieved a record number of FDA-cleared solutions. Medical diagnosis is hitting a breaking point, where the number of physicians hasn't kept up with the rapidly growing patient load. This leads to misdiagnosis and treatment delays that result in hundreds of thousands of deaths every year. Aidoc assists clinicians by precisely highlighting diseases directly on medical images, preventing misdiagnosis and ensuring that urgent patients receive the immediate attention they need. About this role This is a AI Software Tech Lead, ML role within Aidoc’s AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products. Responsibilities • Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging. • Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features. • Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems • Develop and maintain high-quality, scalable, and efficient code. • Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems) Requirements • BA/BSc/MSc in Computer Science, Engineering or a related field. • 7+ years of experience in developing large scale production systems – including architecture design, research, development and testing. • Deep understanding of Computer Science fundamentals – object-oriented design, code optimization, and complexity • Passion for building generic and robust software architecture • Passion for elegant and effective technological solutions, and a love for clean code • Strong experience with Python and advantage to deep learning frameworks such as TensorFlow, PyTorch, etc. • Strong ability to lead end-to-end development processes • Advantage: Experience in developing AI and machine learning solutions, with a focus on computer vision and NLP. • Strong communication and collaboration skills, with the ability to work effectively with a cross-functional team Working at Aidoc Our Perks: • Be part of something big - using cutting-edge technologies to transform the Healthcare industry (while saving patients’ lives) • We work in a hybrid model, with our new offices located at 34 HaMasger Street in Tel Aviv and parking for employees. • Amazing and healthy breakfasts and lunches prepared daily by our personal chef! • Stocked up kitchen & meal card • Wellness: Aidoc employees-only gym, plus Pilates, Yoga, and functional workouts classes. • Amazing culture - collaborative, transparent & fun! • Attractive compensation package & benefits Aidoc is deeply committed to creating an inclusive workplace, and to the principle of equal opportunity for all individuals. We prohibit discrimination and harassment based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by law.

Description Popai is on a mission to transform the millions of conversations that happen between care teams and patients every day. We’re building the AI platform that turns every patient interaction into action - helping care teams understand what patients need, close gaps in care, and reach the people who need them most. Our goal is simple but ambitious: make he As an AI Engineer at Popai, you will design, build, and deploy intelligent systems that power our core product. You will work across the entire lifecycle—from building robust data pipelines for medical records and audio data to operationalizing cutting-edge LLMs and agentic workflows in production. What You'll Do • Build AI & Data Pipelines: Design, build, and maintain data and AI pipelines that ingest, process, and analyze large-scale healthcare data (including medical records, audio signals, and system traffic). • Develop Intelligent Systems: Build systems that extract structured entities, definitions, and actionable insights from complex unstructured data. • Deploy AI Agents: Operationalize and integrate AI agents using LLMs, open-weight models, and specialized tools into production systems to automate reasoning and care workflows. • Optimize Performance: Optimize model performance, inference pipelines, and latency to ensure high scalability and efficiency. • Ensure Data Quality & Observability: Design reliable data workflows with built-in quality checks, consistency, and monitoring across all pipeline stages. • R&D & Innovation: Experiment with emerging AI frameworks, model architectures, and agentic workflows to continuously elevate the platform's intelligence. Requirements What We're Looking For • Experience: 6+ years of hands-on experience as a Software Engineer, AI Engineer, or Data Engineer. • Scalability & Systems: Proven track record of working on high-scale, distributed systems with a focus on performance optimization and resilience. • Data Infrastructure: Solid understanding of data processing and storage technologies (e.g., PostgreSQL, BigQuery, Snowflake, Spark, Kafka). • AI & LLM Deployment: Practical experience integrating, serving, or fine-tuning LLMs and smaller specialized models (API-based or open-weight). • Cloud & DevOps: Proficiency with cloud platforms (AWS, GCP, or Azure) and containerized setups (Docker, Kubernetes). Nice to Have • Experience with LLM serving optimizations, quantization, prompt engineering, or agent orchestration frameworks (e.g., LangChain, LangGraph). • Familiarity with audio/speech processing or medical record data systems. • Experience designing event-driven, streaming architectures. • Background in real-time inference or low-latency AI applications.

Description Bluespine is an innovative startup in the health-IT domain. Using cutting-edge technologies, we build AI-driven systems that find what's going wrong in healthcare spending: billing errors, wasteful care, and potentially fraudulent claims, which together cost the industry billions of dollars every year. We also identify concrete cost-saving opportunities for employers. Each assessment is tailored to the individual claim, taking into account the relevant provider, payer, and plan, so the results are precise and trustworthy. We're looking for a technical builder-leader who pairs strong engineering skills with a passion for AI and a drive to improve real-world processes with it. Responsibilities • Design and build AI agents and automation workflows that analyze claims at scale and find errors, waste, fraud, and savings. • Own the agent harness and the loops around it: how agents plan, call tools, verify their own work, and improve over time. • Build the systems that make experimentation with LLMs, agents, and workflows fast, measurable, and safe to ship. • Develop and validate algorithms that hold up in production, where accuracy matters and every finding has to be explainable. • Investigate, implement, and share new AI technologies and ideas, and set the technical direction for how we use them. Requirements • 5+ years of data science/analysis experience. • 2+ years of software engineering experience (Python, Node.js, Go, or similar). • Hands-on experience building or integrating AI tools, APIs, or agents. • Familiarity with LLM-based patterns such as agentic workflows, harness and loop engineering, and production-level prompt engineering. • Experience with cloud platforms such as AWS, Google Cloud, or Azure. • Strong communication, interpersonal, and problem-solving skills. Advantages • Background in healthcare data or fraud investigations. • Prior experience in health insurance tech or medical coding/billing. • Degree in computer science or equivalent.

Description 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. Requirements 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.

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary Join our Security Autonomous SOC Team as a Principal AI Engineer to transform innovative AI/LLM research into impactful cybersecurity product features. You will leverage and augment our existing infrastructure, including BI systems and CI/CD pipelines, to design, develop, and deploy advanced LLM and Agentic capabilities. Your expertise in software development, AI engineering, and modern LLM technologies will directly drive the evolution of our security operations. By building robust, production-ready AI solutions, you will make a tangible difference in protecting our digital world against complex threats. Key Responsibilities • Design and build Agentic security solutions to improve detection, response, and remediation capabilities. • Architect, implement, and optimize end-to-end LLM pipelines ensuring scalability from data ingestion to deployment. • Develop and deploy AI agents leveraging LLMs to automate complex security decision-making tasks. • Integrate LLM APIs and fine-tune models for specific cybersecurity use cases. • Transform promising AI and LLM research concepts into mature, robust, and scalable production-ready features. • Augment established BI data systems and CI/CD pipelines to support advanced AI development and experimentation. • Develop specialized tools and frameworks extending infrastructure to support AI-driven security research and remediation. • Collaborate with cross-functional teams to integrate AI innovations into customer-facing XDR, EDR, and SOAR platforms. Qualifications Required Qualifications • Minimum of 5 years of proven experience in software engineering and delivering production-ready solutions. • Demonstrated expertise designing, building, and optimizing end-to-end LLM pipelines and AI agents. • Exceptional programming skills in Python with a strong background in robust software development. • Extensive experience with data engineering, CI/CD environments, and cloud platforms like AWS, GCP, or Azure. • Proficiency in containerization technologies, including Docker and Kubernetes, for scaling AI and LLM solutions. • In-depth practical knowledge of AI concepts, LLM APIs, and model fine-tuning techniques. Preferred Qualifications • Familiarity with cybersecurity concepts, security operations, incident response, and advanced threat research. • Hands-on experience working with XDR, EDR, NDR, or SOAR products and understanding attack methods. • Proven ability to innovate independently while collaborating effectively within dynamic, cross-functional engineering teams. • Strong critical thinking mindset with a passion for applying cutting-edge AI to solve complex security challenges. Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [email protected]. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary Your Career: The Cortex Content team powers Palo Alto Networks’ security operations platforms (XSIAM/XSOAR) by building the essential integrations, data connectors, and intelligence layers that protect our customers. We are looking for a Senior Software Engineer who is passionate about AI and automation to help scale our content ecosystem. In this role, your focus will be leveraging AI to accelerate the delivery, quality, and quantity of our security integrations and content infrastructure. You will design and develop intelligent tools and workflows that enable engineering peers and Technical Program Managers (TPMs) to scale their output, collaborating with them as they test, adopt, and integrate these solutions into our development lifecycle. Your Impact: • Scale Content Delivery: Design and implement AI-driven systems that empower the team to significantly increase both the quantity and the rigorous quality of our security integrations. • Develop Cross-Functional Tooling: Build internal developer tools and agentic workflows that enable other engineers and TPMs to streamline content creation, validation, and management. • Optimize Workflows: Create reliable CI/CD pipelines incorporating AI agents to automate code generation and testing processes. • Support Team Adoption: Collaborate with engineering peers and cross-functional partners as they test and integrate your tools into their daily workflows, using their feedback to drive continuous improvements. • Contribute to AI Integration: Help lead the practical integration of LLMs and automation frameworks into our day-to-day engineering processes. Qualifications Your Experience: • Experience: 3+ years of professional software engineering experience delivering clean, maintainable code in a production environment. • Proven AI/Automation Impact: Demonstrated experience in at least one of the following areas: Supported or led an AI transformation/adoption effort within an engineering team. Developed and deployed a major AI-powered feature or internal productivity tool. Built CI/CD workflows or developer tooling that utilizes autonomous AI agents. • Collaborative Mindset: Experience building tooling meant for other technical stakeholders (engineers/TPMs) and incorporating user feedback into future iterations. • Core Engineering Skills: Solid understanding of software design, API development, and data workflows. Nice to Have: • Python Proficiency: Strong experience with Python and its associated libraries or AI frameworks (e.g., FastAPI, LangChain, or similar orchestration tools). • Security Knowledge: Familiarity with SIEM, API integrations, or general cybersecurity operations. Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [email protected]. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.

Description Upwind is a next-generation Cloud Security Platform that uses runtime context to identify and prioritize critical risks. Unlike traditional tools, Upwind uses runtime data to prioritize risk and inform posture, so teams can focus on what truly matters. Our eBPF-powered sensors and agentless cloud discovery deliver real-time threat protection, posture management, and API security. Together they protect cloud infrastructure end to end, from misconfigurations to malware. At Upwind, you'll have room to think creatively, explore new ideas, and make a real impact on our growth. We're looking for a hands-on AI Engineer to join Upwind's Research team. You'll help build our core intelligence engine: LLM agents that run cloud security workflows end to end. These agents investigate runtime detections, reason over workload, identity, and cloud context, and drive remediation in production. You'll research new models and agent designs, run rigorous experiments, and ship what works as high-impact features in our platform. What you will do • Build LLM-based agents that investigate, triage, and remediate cloud security threats. • Own the path from research to production: prototype new models, techniques, and agent designs, and ship the ones that work. • Train, fine-tune, and evaluate models for security tasks using Upwind's vast data sources: runtime events, cloud logs, identity, and network activity. • Build and extend our internal AI platform: services, pipelines, evals, and observability. • Collaborate with Security Researchers, Product, and Engineering to turn research findings into production-grade autonomous workflows. Requirements • 3+ years building AI/ML systems in production, including LLM-based agents built with modern AI and agent frameworks. • Strong backend engineering skills and proficiency in Python. • Experience training or fine-tuning ML models and LLMs. • Strong understanding of AI system reliability: prompting and context engineering, evaluation pipelines, LLM-as-judge, regression testing, and production monitoring. • Proven AI research ability: track the literature, frame open problems, design rigorous experiments, and benchmark new techniques against the state of the art. • Strong ownership and the ability to work both independently and as part of a team in a fast-paced environment, bridging research and product engineering. • Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Nice to have • Background in cybersecurity (e.g., cloud security, threat detection, incident response). • Hands-on experience with cloud platforms (AWS, GCP, Azure) and Kubernetes. • • Research publications, open-source contributions, or other work that shows depth in AI.

Description Upwind is a next-generation Cloud Security Platform that leverages runtime context to identify and prioritize critical risks, providing precise insights and efficient cloud security management. Unlike traditional tools, Upwind uses runtime data proactively for risk prioritization and posture insights, ensuring teams focus on what truly matters. With industry-leading efficiency and eBPF-powered sensors, Upwind delivers comprehensive capabilities, including agentless cloud posture discovery, real-time threat protection, and integrated API security. From misconfigurations to malware defense, Upwind ensures end-to-end, cost-effective cloud infrastructure protection. At Upwind, you'll have the opportunity to work on some of the most challenging problems in applied AI and security, turning cutting-edge research and LLM capabilities into products that operate in real customer environments. We're looking for an AI Engineering Lead to help drive the quality, intelligence, and continuous improvement of Upwind's AI and agentic systems. This is a hands-on AI engineering lead role focused on data, evaluation, and agentic workflows. You'll build the systems and methodologies that allow us to understand how our agents perform, identify where they fail, and continuously improve their reasoning, tool usage, and outcomes. You'll work closely with AI Researchers, Engineers, and Product teams to turn experiments into reliable, high-performing AI systems — from defining evaluation datasets and metrics to improving agentic workflows and deploying them at scale. What You’ll Build: • Agentic Workflows: Design and continuously improve multi-step agent workflows, including reasoning, tool usage, planning, state management, and recovery strategies. • AI Evaluation: Build evaluation frameworks, datasets, metrics, and automated pipelines to measure the quality and reliability of LLMs and agents. • AI Data Infrastructure: Build the data pipelines and feedback loops required to collect, curate, analyze, and learn from real-world agent interactions • AI Observability: Build visibility into agent behavior and performance, including trajectories, tool calls, latency, failures, and outcome quality. Responsibilities: • Own and evolve the evaluation strategy for Upwind's AI agents and LLM-powered features. • Define meaningful metrics and automated evaluation pipelines for measuring agent quality, accuracy, reliability, and task completion. • Design and improve agentic workflows to make agents more capable, reliable, efficient, and predictable. • Build feedback loops from production usage back into evaluation datasets and development workflows. • Develop tooling for running experiments and comparing models, prompts, workflows, and agent configurations. • Work closely with AI Researchers to turn research ideas and experiments into production-quality AI capabilities. • Collaborate with backend engineers to integrate AI workflows and evaluation systems into our production platform. • Establish best practices for testing and validating non-deterministic AI systems. • Monitor AI systems in production and continuously identify opportunities for improvement. • Take end-to-end ownership of projects- from defining the problem and building the first experiment to productionizing and measuring its impact. Requirements • Strong engineering experience, with a track record of owning and delivering complex technical systems. • Hands-on experience building LLM-powered applications, agents, or AI systems. • Strong understanding of LLM evaluation, experimentation, and data-driven development. • Experience designing and implementing LLM-as-a-Judge evaluations, including evaluation criteria, scoring rubrics, structured outputs, and validation of judge reliability. • Strong problem-solving skills and the ability to analyze complex AI behavior and turn observations into concrete improvements. • Experience working with agentic workflows, tool calling, multi-step reasoning, or AI orchestration. • Ability to work closely with researchers and engineers and bridge the gap between experimentation and production. • Comfortable working in a fast-paced environment where requirements and technologies evolve quickly. Strong Advantages: • Experience with LLM evaluation frameworks and automated evaluation pipelines. • Proven experience with LLM-as-a-Judge methodologies, including calibrating judges against human evaluations, measuring evaluator consistency, and reducing evaluation bias • Experience with LangGraph, LangChain, or comparable agent orchestration frameworks. • Experience working with security, infrastructure, or other complex technical domains. • Experience building production AI systems where correctness and reliability are critical. • Strong Python skills and experience working with data processing and AI/ML tooling. Why Upwind? • You'll have the opportunity to work on AI systems that are solving real, complex security problems- not demos or prototypes. • You'll be part of a team building the next generation of AI-powered security agents, with the opportunity to influence how we evaluate, improve, and scale these systems from the ground up.

Description We Are KPMG Israel. KPMG Israel is more than a professional services firm, we are a community of people driven by impact. As part of a leading global network, we partner with the most influential organizations to drive large-scale business and technology transformation, combining strategic thinking, innovation, and advanced technologies. Guided by integrity, excellence, and forward thinking, we help organizations navigate complexity and create real change. Our people are at the center, with space to lead, experiment, and grow in a dynamic and collaborative environment that connects personal development with meaningful impact on the future of business and society. We are seeking an experienced Generative AI Engineer to join our AI squad at KPMG. This is a unique opportunity to wear multiple hats - serving as both a developer of cutting-edge GenAI solutions and an advisory expert helping organizations transform their AI capabilities. You'll build end-to-end GenAI projects from conception to production while staying at the forefront of this rapidly evolving field. Key Responsibilities GenAI Development & Implementation • End-to-End Development: Build GenAI solutions from POC through production deployment, handling all backend development responsibilities • Client Engagement: Participate in technical discussions with clients, gather requirements, and help translate business visions into feasible technical solutions through presentations and consultations • Backend Development: Design and implement production-grade microservices architectures for GenAI applications using Python • Cloud Implementation: Deploy and manage GenAI solutions across GCP, Azure, and AWS platforms, leveraging cloud-native AI services • Cross-functional Collaboration: Work closely with project managers, full-stack developers, and Power Automate teams to deliver complete solutions • System Evaluation: Assess and optimize production-grade GenAI systems for performance, scalability, and reliability Continuous Learning & Innovation • Technology Scouting: Continuously explore and evaluate new GenAI models, frameworks, and techniques as they emerge • Best Practices Development: Establish and refine methodologies for GenAI solution development and deployment Requirements Technical Expertise: • Programming: Advanced proficiency in Python for backend development and AI applications • GenAI Mastery: Deep understanding of large language models (LLMs) and experience with major model APIs (OpenAI, Anthropic, Google, etc.) • Multi-Agent Systems: Expertise in designing and implementing GenAI multi-agent architectures • Prompt Engineering: Advanced skills in prompt design, optimization, and engineering techniques • Cloud Platforms: • Required: Hands-on experience with AI services in at least one major cloud platform (GCP, Azure, or AWS) • Advantage: Experience across multiple cloud platforms (AI Search, Vertex AI, SageMaker, etc.) • Development Frameworks: Experience with GenAI frameworks like LangChain and cloud-based retrieval services • Software Engineering: Strong background in microservices architecture, API development, and production system design • AI/ML Fundamentals: Solid understanding of deep learning principles and GenAI techniques • Containerization (Advantage): Experience with Docker and Kubernetes for deployment and orchestration • OCR Technologies (Advantage): Experience with Optical Character Recognition systems and document processing • Data Pipelines (Advantage): Experience building and maintaining data processing pipelines Professional Experience • Mid+ Level Experience: 2+ years in AI/ML development with significant GenAI project experience • Production Systems: Proven track record of deploying and maintaining AI solutions in production environments • Client-Facing Experience: Comfortable with technical presentations and requirement gathering sessions Education & Background • Preferred: Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related technical field • Alternative: Demonstrated industrial experience in developing deep learning and GenAI solutions (degree not required with strong portfolio) Soft Skills • Problem-Solving: Excellent analytical and creative problem-solving abilities • Communication: Strong technical communication skills for both technical and non-technical audiences • Collaboration: Proven ability to work effectively in cross-functional teams • Adaptability: Thrives in fast-paced environments and eager to learn emerging technologies • Consulting Mindset: Ability to understand client needs and provide strategic technical guidance What We Offer • Opportunity to work on cutting-edge GenAI projects across diverse industries • Dual role combining hands-on development with strategic consulting • Access to latest AI technologies and cloud platforms • Collaborative environment with cross-functional teams • Professional development in a rapidly evolving field Diversity & Inclusion This position is open to all qualified candidates. We support diversity and view it as a strength that enhances our ability to develop, learn, and innovate. We advocate for inclusion and empower people of all backgrounds to contribute their unique perspectives.

ScaleOps is redefining autonomous cloud and AI infrastructure. We're on a mission to free DevOps and platform engineers from manual resource management so they can focus on innovation, not tuning resources. The results: maximized performance and a reduction of cloud costs by up to 80%. As the category leader in Autonomous Cloud and AI Infrastructure Resource Management, we're trusted by leading enterprises including Adobe, Wiz, Epic Games, Northwestern Mutual, Coinbase, DocuSign, and Fortune 100 companies to autonomously manage their most critical production environments. Backed by Insight Partners, Lightspeed Venture Partners, and other leading VCs with over $210M in funding, ScaleOps is the leading player in a massive and growing market. We are building the autonomous infrastructure management platform that will power the next decade of enterprise compute. What You'll Be Doing • Lead the AI Platform team: own the internal platform ScaleOps R&D builds on, including CI/CD, Kubernetes tooling, developer experience, and infrastructure automation • Stay hands-on while leading the team day to day: delivery, technical decisions, and hiring • Build and connect AI tools for R&D and the company, and bring new tools and best practices from the market into how we build the product • Build infrastructure for the other R&D teams, from internal agentic platforms to the foundations that LLM-powered automation runs on • Partner closely with backend, product, and R&D teams, and treat engineers as your customers: measure adoption and time saved • Identify and eliminate friction in the development lifecycle through automation and self-service tooling What You'll Bring • 5+ years of hands-on experience in platform engineering, infrastructure, or AI/ML infrastructure in high-scale environments • 2+ years of proven experience leading software engineering initiatives and mentoring engineers in a production environment • Experience building self-service platforms or tooling that other engineers adopted • Strong hands-on experience with Kubernetes, cloud (AWS, GCP, or Azure), and infrastructure-as-code • Strong development skills: you have written production code, ideally Go, such as Kubernetes operators or controllers • A builder mindset, strong ownership, and curiosity about the AI market and its tooling • Full professional fluency in Hebrew and English (ב-US: “Full professional fluency in English”) • (Nice to have) Open-source contributions in the cloud-native space (Karpenter, Cilium, KEDA, Argo, Kueue) • (Nice to have) Experience with LLM serving, agentic frameworks, or MCP-based tooling • (Nice to have) Experience with scheduling, node lifecycle, or resource management in Kubernetes

ScaleOps is redefining autonomous cloud and AI infrastructure. We're on a mission to free DevOps and platform engineers from manual resource management so they can focus on innovation, not tuning resources. The results: maximized performance and a reduction of cloud costs by up to 80%. As the category leader in Autonomous Cloud and AI Infrastructure Resource Management, we're trusted by leading enterprises including Adobe, Wiz, Epic Games, Northwestern Mutual, Coinbase, DocuSign, and Fortune 100 companies to autonomously manage their most critical production environments. Backed by Insight Partners, Lightspeed Venture Partners, and other leading VCs with over $210M in funding, ScaleOps is the leading player in a massive and growing market. We are building the autonomous infrastructure management platform that will power the next decade of enterprise compute. What You'll Be Doing • Build and run the internal platform ScaleOps R&D builds on: CI/CD, Kubernetes tooling, developer experience, and infrastructure automation • Give every engineer a fast, safe path to develop, test, and ship code to production • Build and connect AI tools for R&D and the company, and bring new tools and best practices from the market into how we build the product • Build infrastructure for the other R&D teams, from internal agentic platforms to the foundations that LLM-powered automation runs on • Partner closely with backend, product, and R&D teams, and treat engineers as your customers: measure adoption and time saved • Identify and eliminate friction in the development lifecycle through automation and self-service tooling What You'll Bring • 5+ years of hands-on experience in platform engineering, infrastructure, or AI/ML infrastructure in high-scale environments • Experience building self-service platforms or tooling that other engineers adopted • Strong hands-on experience with Kubernetes, cloud (AWS, GCP, or Azure), and infrastructure-as-code • Strong development skills: you have written production code, ideally Go, such as Kubernetes operators or controllers • A builder mindset, strong ownership, and curiosity about the AI market and its tooling • Full professional fluency in Hebrew and English (ב-US: “Full professional fluency in English”) • (Nice to have) Open-source contributions in the cloud-native space (Karpenter, Cilium, KEDA, Argo, Kueue) • (Nice to have) Experience with LLM serving, agentic frameworks, or MCP-based tooling • (Nice to have) Experience with scheduling, node lifecycle, or resource management in Kubernetes

ScaleOps is redefining autonomous cloud and AI infrastructure. We're on a mission to free DevOps and platform engineers from manual resource management so they can focus on innovation, not tuning resources. The results: maximized performance and a reduction of cloud costs by up to 80%. As the category leader in Autonomous Cloud and AI Infrastructure Resource Management, we're trusted by leading enterprises including Adobe, Wiz, Epic Games, Northwestern Mutual, Coinbase, DocuSign, and Fortune 100 companies to autonomously manage their most critical production environments. Backed by Insight Partners, Lightspeed Venture Partners, and other leading VCs with over $210M in funding, ScaleOps is the leading player in a massive and growing market. We are building the autonomous infrastructure management platform that will power the next decade of enterprise compute. What You'll Be Doing We're forming a new AI Group and looking for a Senior AI Engineer to help shape it from an early stage - a greenfield, long-term effort to evolve how decisions are made across the ScaleOps platform using AI-driven systems. You won't just integrate APIs or build demos; you'll build the AI brain that works alongside (and increasingly drives) our core automation engine, with real production impact from day one and room to grow into technical leadership as the group scales. • Agentic AI Architecture: Design and build autonomous AI agents that analyze infrastructure in real time and make intelligent decisions. Work with modern agentic frameworks (LangGraph, PydanticAI) and conversational AI to create multi-agent systems - including troubleshooting, optimization, FinOps, and how-to agents. Leverage core LLM capabilities (tool-use, memory, retrieval) to operate safely in production. • Platform Integration & Intelligent Decision Systems: Develop MCPs to expose ScaleOps capabilities to AI agents that reason over infrastructure environments, metrics, configurations, and cost signals. Build integrations with tools like Slack, Jira, and AI-powered IDEs (Cursor, Windsurf) to deliver context-aware insights, from "why is this pod not scheduling?" to "how can we reduce costs by 30% safely?" • AI Model Development & MLOps: Build and deploy machine learning models that learn from infrastructure patterns - detecting the right resource policies for workloads, predicting optimal scaling triggers, and recommending GPU configurations. Own the complete ML pipeline from training to production, ensuring models are reliable, monitored, and continuously improving. • R&D AI Tools Development & Adoption: Build and embed internal AI tools to accelerate engineering, development, research, and support. • AI Tools for Business Impact: Develop AI-powered tools that help Sales and Support teams demonstrate value instantly - agents that analyze customer infrastructure, generate cost optimization reports automatically, and turn technical data into clear business recommendations. • End-to-End Ownership: Own AI systems from concept to production, ensuring they're fast (sub-2-second responses), reliable, safe, and cost-effective. Build evaluation frameworks to measure quality, implement security controls, and balance performance tradeoffs in production. • Technical Leadership: Define AI architecture and best practices as a founding member of the AI team. Make key technical decisions - choosing frameworks, designing multi-agent systems, establishing data governance - and shape how ScaleOps evolves from AI-enhanced internal tools to customer-facing AI products. What You'll Bring • Core Engineering: Significant software engineering experience (typically 4+ years) with strong Python skills and solid backend engineering fundamentals. • Production Experience: Experience building and operating production systems in cloud environments. • Real-World GenAI Experience: Practical experience bringing LLM-based systems into production, including handling latency, cost control, and failure modes. Familiarity with additional agentic frameworks (e.g., LangChain, MetaGPT) and evaluation frameworks. • Builder Mentality: Strong ownership and the ability to operate independently while collaborating closely across teams, with the motivation to grow into technical leadership as the group expands. • (Advantage) Data & RAG: Experience enabling LLMs to consume structured or operational data (configurations, logs, metrics) and experience with retrieval systems (RAG) or vector databases.

Job Description • Agentic Framework Design: Design and implement intelligent, multi-agent AI systems capable of executing complex security analysis workflows and automated decision-making. • Context Optimization: Analyze diverse security datasets to determine the most effective context, telemetry data, and threat intelligence to feed into AI agents to maximize decision accuracy and minimize false positives. • Model Configuration & Integration: Evaluate, configure, and deploy a variety of state-of-the-art language models and AI architectures tailored for high-performance security use cases. • Data Analysis & Performance Evaluation: Perform deep data analysis on security events and model outputs to continuously refine agent logic, benchmark performance, and optimize AI-driven detection mechanisms. • Collaboration & Deployment: Partner with security research and engineering teams to integrate intelligent AI components into production systems seamlessly and securely. Qualifications Required Technical Skills • AI & Agentic Systems: Proven experience building applications with modern AI architectures, advanced prompt engineering, and multi-agent orchestration frameworks. • Model Management: Hands-on experience configuring, optimizing, and deploying diverse machine learning and language models. • Data Processing & Analysis: Strong proficiency in Python and data analysis libraries to manipulate, clean, and extract insights from high-velocity data streams. • Security Awareness: Familiarity with cybersecurity concepts, threat detection principles, or common security data formats (such as system logs, event tracking, or endpoint telemetry). Preferred Qualifications & Advantages • SLM & Local Deployment: Direct experience working with, optimizing, and deploying Small Language Models (SLMs) to run efficiently in local or resource-constrained environments. • Analytical Thinker: Exceptional problem-solving skills with the ability to diagnose complex system behaviors and iteratively improve AI model performance based on data. • Adaptability: Passion for staying at the absolute forefront of rapidly evolving AI technologies and applying them creatively to complex domains. • Experience: 3+ years of professional experience in data science, AI engineering, or related technical fields, with a proven track record of deploying AI-driven solutions. • Education: Bachelor’s degree in Computer Science, Data Science, Cybersecurity, or a related quantitative field (or equivalent practical experience) from a recognized and accredited university.

Realize your potential by joining the leading performance-driven advertising company! As a Senior GenAI Engineer in our GenAI team in the Tel Aviv office, you’ll play a key role in developing and enhancing our generative AI products, building advanced algorithmic solutions that improve content discovery, personalization, and monetization at scale. To thrive in this role, you’ll need: • M.Sc. in Computer Science, Mathematics, Engineering, or a related field • Strong Python, SQL and Spark skills • Familiarity with statistical modeling techniques • 2+ years of hands-on experience designing, building and evaluating GenAI workflows, including Agentic RAG, Tool calls evaluation, LLM-as-a-judge, RLHF, and LLM fine-tuning • 3+ years of experience in data science, analytics, and visualization • Excellent problem-solving and critical-thinking abilities • 3+ years of hands-on experience developing traditional machine learning algorithms, and NLP models. Bonus points if you have: • Strong mentoring and public-speaking skills, with a passion for writing research papers and technical documentation and sharing knowledge at conferences. • Experienced in Java or Scala How you’ll make an impact: • Be responsible for the entire algorithmic lifecycle of our user facing multilingual GenAI product at scale DeeperDive: data analytics, offline and online evaluation of new LLMs, evaluate the quality of our generative content, minimize hallucinations, evaluate guardrails, tool use and router calls, and improve retrieval combined with NER. • Improve personalized monetization flows and impact directly on the company’s revenue. • Work on a daily basis with on prem LLMs hosted in our datacenters, cooperate with external providers and embrace SOTA technologies. • Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems • Influence directly on the way billions of people discover the internet. • Work on projects such as DeeperDive, LLM monetization, Personalized user questions, organic recommendations and personalized ads. Our tech stack: Python, Java, Langfuse, TensorFlow, Spark, Kafka, Cassandra, HDFS, iceberg, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes and Docker. Why Taboola? If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about: • Adam Singolda, Taboola Founder and CEO: “You can copy anything from another business but you can’t copy a company’s culture.” • Well-being: Competitive benefits and well-being programs tailored to the region, including comprehensive health benefits, a fully stocked kitchen, and location-specific perks. • Flexibility: We offer a hybrid work schedule with 3 days in-office, with an option to come in more often if desired. • Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, and Expedia. Ready to realize your potential? Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need. Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog. About Taboola Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale. Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale. About DeeperDive DeeperDive is a 10M monthly active users RAG based generative AI answer engine designed specifically for trusted publishers. It delivers concise, real-time answers that reflect what audiences are actively reading - surfacing not only what happened, but why it matters. Built on Taboola’s “Pulse of the Internet” - insights from over 600 million daily users — DeeperDive helps publishers respond to trending questions and deliver meaningful context on the topics their readers care about most. Rather than replacing journalism, DeeperDive enhances it. It empowers newsrooms to produce credible, nuanced content at scale, while preserving each publisher’s unique editorial voice and brand integrity. #LI-DN1 #LI-Hybrid