Top Artificial Intelligence Jobs in Israel

Design and build scalable, secure cloud platform infrastructure for AI-driven SaaS cybersecurity products. Responsibilities include developing microservices, enabling CI/CD and DevOps processes, improving performance and reliability, collaborating across engineering teams, establishing backend engineering best practices, reviewing designs, mentoring engineers, and leading Agile projects involving high-scale, low-latency systems.

Develop and productionize ML/AI models for sensitive data classification and insights. Own end-to-end lifecycle from problem framing, data strategy, model development, evaluation, deployment, and monitoring. Build deep learning and NLP solutions, agentic workflows, and rigorous evaluation pipelines for scalable, production-ready systems.

Own Pentera’s internal AI transformation strategy and build production AI agents, context layers, retrieval systems, action tools, and evaluation and safety infrastructure. Set architecture, model, vendor, ROI, security, and quality standards while partnering with business teams to scale successful workflows. Mentor AI Champions, advise leadership, and establish reusable internal AI platform patterns.

Leads the design, development, deployment, and scaling of generative AI platforms and systems. Responsibilities include building Python-based microservices, applying LLM, RAG, fine-tuning, and inference techniques, designing secure APIs, implementing DevOps practices, collaborating with product and business teams, solving complex technical problems, and mentoring engineers.

Develop and automate application security tooling, workflows, and AI security agents. Conduct secure code reviews, manage vulnerabilities, promote secure coding standards, and integrate security into R&D and DevOps processes. Build capabilities for detecting malicious activity, triaging alerts, and investigating incidents. The role also includes documenting security product requirements and securing LLM-based and agentic applications across cloud-native environments.

Lead the vision, roadmap, and architecture of AI-driven data-center networking solutions, including LLM troubleshooting, predictive resiliency, AIOps, optimization, and performance tuning. Collaborate with engineering, reliability, research, product, architecture, and data teams to integrate AI into networking systems and workflows. Identify opportunities for automated failure management, troubleshooting, resource optimization, and performance improvement while translating system behavior and operational constraints into research problems.

Own cloud features end to end, including architecture, backend services, React interfaces, database design, testing, CI/CD deployment, monitoring, troubleshooting, and production support. Use AI coding tools such as Claude Code, Cursor, and GitHub Copilot to accelerate development. Collaborate with Product and UX teams to deliver scalable, reliable customer experiences on public cloud platforms.

Create and prototype interactive web games and experiences using AI-assisted development tools. Translate creative ideas into polished gameplay, visuals, animation, effects, and interactions while experimenting with AI, creative coding, and real-time web technologies. Collaborate with artists, designers, and developers to improve game feel, visual quality, and polish.

Join Welo Data’s global contributor network for flexible, remote AI projects involving text, image, and audio annotation; search, advertisement, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. Native or near-native Hebrew, English proficiency, digital tool comfort, and strong attention to detail are required.

Develop and optimize high-performance real-time digital processing software for 4G baseband modems and carrier-grade cellular PHY systems. Responsibilities include debugging, root-cause analysis, module integration, product bring-up, software architecture, testing, and applying agentic development and LLM-based workflows. The role requires strong C++ and Python skills, object-oriented design, CI/CD, Git, and Agile practices, with preferred experience in Arm, SIMD, Kubernetes, MATLAB, and 4G/5G standards.

Leads PHY and RF system engineering for next-generation Open RAN base stations. Responsibilities include defining system requirements, optimizing PHY algorithms, integrating PHY components with hardware, software, and DSP subsystems, building automation and testing tools, using AI-assisted development workflows, conducting lab validation, and mentoring junior engineers.

Lead the architecture, development, optimization, testing, and production support of LTE Layer 1 PHY software for carrier-grade Open RAN systems. Drive real-time performance, debugging, and technical roadmaps while mentoring engineers and collaborating across MAC, systems, integration, QA, and product teams. Apply agentic software development and LLM-based workflows to accelerate engineering delivery.

Own end-to-end consumer growth, including acquisition, onboarding, retention, funnel optimization, and rapid experimentation. Build AI-powered automations, pipelines, landing pages, interactive experiences, sub-products, and custom workflows using modern AI builder tools. Analyze conversion data, make fast decisions, lead cross-functional initiatives, and potentially manage junior growth builders or a future growth team.

Build and deploy production-grade LLM applications, RAG systems, agentic workflows, and internal AI tools. Evaluate foundation models, develop tool-using and multi-agent systems, improve reliability and reduce hallucinations, and establish evaluation methodologies for quality and safety. Collaborate with algorithms, mapping, software, and research teams to transition prototypes into scalable products.

Architect, deploy, and test AI-powered cybersecurity solutions in virtualized digital twin environments. Configure infrastructure for large language models, fine-tune NVIDIA Nemotron models, manage security datasets, and automate CI/CD testing, validation, and benchmarking pipelines. The role requires collaboration with data scientists, security architects, offensive security researchers, and global engineering teams while troubleshooting operating systems, kernels, services, and physical or virtual networking.

Design, architect, and scale backend platforms powering GenAI copilots and agentic decision flows. Build secure, resilient microservices and distributed systems that consolidate complex data for investigative analytics. Integrate AI models into high-performance production systems, collaborate with Data Science and Product teams, own critical components, maintain software stability, and mentor engineers. The role requires Java development, cloud-native technologies, messaging systems, relational and NoSQL databases, and experience operating high-velocity production environments.

Own the Data and AI product domain across the full lifecycle. Define product strategy, AI model integration and behavior, data analytics capabilities, and the roadmap for cybersecurity products. Partner with R&D, Sales, and customers to gather market insights, deliver AI/ML-driven features, and drive product adoption, revenue, and ongoing success.

Designs and builds reusable AI platform capabilities, production-grade agentic systems, internal AI tools, and shared AI services. Integrates emerging models and frameworks, develops end-to-end AI architectures, and operates scalable cloud-native AI systems. The role improves reliability and observability, establishes engineering standards, leads technical proofs of concept, drives adoption, collaborates with Data Science teams, and mentors engineers.

Build and ship internal AI agents, applications, intelligent workflows, and shared AI infrastructure. Own solutions end to end, from problem definition and architecture through implementation, evaluation, logging, deployment, and production support. Integrate AI with company data, APIs, and internal systems; prototype emerging technologies; collaborate directly with internal users; and develop evaluations and guardrails for reliable non-deterministic systems.

Own Sedric’s AI reference architecture across services, agents, retrieval systems, evaluation pipelines, and infrastructure. Define reusable patterns and standards, lead architecture reviews, evaluate vendors and foundation models, and shape the technology roadmap. Build production agentic systems, governance frameworks, and evaluation harnesses while partnering with Product, Engineering, customers, and executives. The role combines hands-on delivery with organization-wide technical leadership, including shipping LLM improvements and optimizing latency and reliability.

Leads the HR Technology Center of Excellence and advises senior leaders on HRIS strategy, governance, risk, controls, and technology roadmaps. Owns complex issues across Workday, payroll, and downstream systems while driving AI, analytics, process improvement, data integrity, compliance, and global operating standards. Partners with HR, IT, Finance, business leaders, and vendors to implement scalable technology-enabled transformations across North America, Europe, and Asia.

Build end-to-end customer-facing AI products and agentic systems. Design orchestration, APIs, and distributed services; implement React frontends and Python backends; deploy scalable microservices on AWS with Docker and Kubernetes; improve reliability, observability, and production performance for continuous shipping.

Lead the AI Platform development team and own architecture for a scalable, cloud-based AI cybersecurity platform. Build AI agents, skills, MCPs, plugins, and infrastructure supporting agentic development, while improving developer experience, quality, security, performance, and delivery velocity. Mentor and hire engineers, establish best practices, manage the platform roadmap, lead Agile projects, and collaborate with development and DevOps teams on high-scale, low-latency systems.

Develop AI agents to automate document processing and optimize human tasks, partnering with teams to identify automation opportunities and conducting extensive testing of AI systems.

Own customer-facing AI and CRM solutions, translate business needs into AI agents and automated workflows, lead implementations, coordinate with development teams, and improve internal processes using AI while managing customer relationships.