Top Artificial Intelligence Jobs in Jerusalem

Lead technical direction for HiBob's AI domain: design scalable AI and agentic architectures, own cross-team initiatives, drive decisions around LLMs, retrieval, tool calling, MCP and evaluation frameworks, mentor engineers, and ensure production-grade reliability and scalability.

The role involves managing the AI platform roadmap, defining reusable AI capabilities, collaborating with engineering, and shaping AI standards within the product ecosystem.

Design, build, and maintain backend infrastructure and microservices enabling AI-driven features. Integrate AI models, develop APIs and data pipelines, ensure performance and resilience, drive engineering excellence, and mentor other backend developers.

Lead and manage all global legal and compliance functions, advising executives on commercial, M&A, contracts, AI/privacy, and regulatory risk. Oversee legal governance, statutory filings, policies, and a global legal team while supporting growth, partnerships, and cross-border operations.

The Head of Digital Acquisition will lead HiBob's global paid growth engine, optimize paid media campaigns, mentor a team, and drive pipeline growth across segments.

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.

Lead end-to-end product for an agentic natural-language-to-quantum-program experience: define roadmap, plugin/dev-tools integration, internal harness, eval metrics, user discovery, and cross-functional delivery sequencing.

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.

The AI Architect will lead AI architectural guidance, hands-on innovation, and establish best practices for AI development while ensuring compliance with regulations.

The AI Software Engineer will optimize computer vision pipelines for edge systems, ensuring performance and reliability while processing real-time maritime video streams.

Develop and maintain Agentic AI components including multi-agent orchestration and RAG workflows. Implement backend logic and data processing in Python and SQL, integrate systems via APIs, write specs and tests, support debugging and production issues, collaborate with global teams, engage end users, and document solutions.

The Head of AI & Automation will lead MAËLYS' AI transformation by defining strategy, building AI solutions, and driving business impact across functions.

Own AI deployment methodologies, standards, governance, and best practices across the organization. Guide teams designing and implementing AI solutions, coordinate cross-functional stakeholders, support project execution, manage risks and dependencies, and develop playbooks, architectures, templates, training, and knowledge-sharing programs. Ensure AI implementations are consistent, scalable, reliable, and production-ready while enabling teams to apply modern approaches including RAG, prompting, agents, and guardrails.

The role involves conducting simulated cyber attacks, vulnerability assessments, risk analyses, and developing mitigation strategies for AI security technologies.

As a CBRN expert at Alice.io, you will evaluate and create prompts for Generative AI systems, ensuring their safety and accuracy in CBRN contexts. You'll provide expert feedback and stay updated with relevant research and regulations.

Build and extend a production LLM agent platform: design agents and tools, implement integrations, own RAG ingestion and retrieval, define integration contracts, drive evaluation-led development, operate deployments and observability, and establish AI-specific engineering practices across frontend and backend.

The AI Operations Engineer will automate workflows, build AI agents, and integrate tech solutions to improve operational efficiency in healthcare at Droxi.

Develop and implement novel machine learning algorithms and foundation-model components for biomedical/clinical outcome prediction. Lead research, experimentation, distributed training, benchmarking, and production-quality implementation while collaborating with cross-functional teams and contributing to publications and IP.

Lead a hands-on engineering squad building real-time, decision-making AI systems at scale. Own architecture, ship critical system components, mentor engineers, embed AI into team workflows, and define the engineering culture and processes.

As an AI Forward Deployed Engineer, you will embed with strategic accounts to build AI solutions that address procurement challenges, while managing customer relationships and delivering outcomes.

Nebius seeks a Senior ML Engineer for AI R&D focusing on applied research in reinforcement learning and agent training, requiring deep expertise in machine learning and software engineering.

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The engineer will optimize AI libraries and components for unique hardware, focusing on performance improvements in AI models and kernels.