Top Artificial Intelligence Jobs in Jerusalem

Analyze product usage and AI model performance to guide product strategy and growth. Build executive dashboards, semantic layers, KPI definitions, event-tracking schemas, and user journey analyses. Identify adoption gaps, measure feature and roadmap impact, evaluate AI outputs, and improve prompt engineering. Partner with Product and Technology leadership to standardize metrics, enable self-service data discovery, and translate complex findings into actionable recommendations.

Own a portfolio of conversational AI products from opportunity identification through launch, scaling, and iteration. Define success metrics, monitor performance, improve conversational quality, and manage hallucination and renter feedback metrics. Translate partner, operations, and user feedback into roadmaps, PRDs, and Jira tickets. Collaborate closely with Engineering and Data Science on experiments, labeling, evaluation loops, engine improvements, and new AI capabilities. The role requires hands-on execution, deep product expertise, and comfort with ambiguity.

Lead complex, cross-functional technology programs across AI, software, robotics, vehicle hardware, infrastructure, simulation, data, and product teams. Own project delivery, improve efficiency, coordinate stakeholders, manage risks and dependencies, align programs with business goals, and drive continuous improvement. The role requires strong technical judgment, systems thinking, communication, influence, and experience delivering complex software or technology programs in fast-paced environments.

Lead Atera’s North American channel sales strategy and partner ecosystem. Recruit and onboard VARs, distributors, and ISVs; develop joint business plans and go-to-market programs; own quota, partner-sourced pipeline, forecasting, and revenue targets; lead co-selling with enterprise sales teams; enable partners through training and sales plays; and collaborate with product, marketing, sales, and operations to build scalable channel processes and playbooks. Travel across the US is required.

Design, build, and maintain backend infrastructure and microservices for AI-driven features. Integrate AI models and services with core systems, develop APIs and data pipelines, and optimize real-time processing for performance, scalability, and resilience. Lead architecture discussions, code reviews, testing, deployment automation, and engineering best practices while mentoring backend developers. This is a nine-month temporary maternity-leave position.

Own the AI platform roadmap and develop reusable capabilities such as retrieval, embeddings, scoring, and agent tooling. Partner with engineering, data, and product teams on architecture, governance, evaluation, monitoring, safety, cost, and transparency. Enable adoption of AI capabilities across products, improve developer experience, and establish standards for building reliable AI systems in production.

Own global paid acquisition strategy and execution across Google Ads, LinkedIn Ads, and other channels. Manage multi-region budgets to drive pipeline, revenue, and ROI; partner with cross-functional teams; integrate AI into campaign optimization, targeting, reporting, and workflow automation; and lead experimentation across campaigns, audiences, creatives, and landing pages.

Lead the technical direction of an AI platform domain, designing scalable architectures and production-ready agentic systems. Drive decisions involving LLMs, retrieval, tool calling, MCP, evaluation frameworks, and AI infrastructure. Own cross-team initiatives from design through production, establish engineering standards, mentor teams, conduct architecture reviews, evaluate emerging technologies, and balance rapid experimentation with reliability, scalability, and production quality.

Develop embedded software for computer vision components within Innoviz’s LiDAR-based embedded solutions. Responsibilities include implementing computer vision software, defining embedded constraints and implementation details for algorithm teams, and debugging advanced object detection and classification systems used in automotive and autonomous driving applications.

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.

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.

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.

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.

Creates high-quality marketing and brand assets across digital, web, event, and campaign channels. Uses generative AI and modern creative tools to explore concepts, produce variations, and scale creative output. Partners with marketing teams on visual storytelling, maintains brand consistency, and develops physical event experiences such as booths, signage, and environmental branding. Evaluates emerging tools and workflows to improve design quality, speed, and impact.

Owns the roadmap and product lifecycle for AI usage control within an enterprise cybersecurity platform. Responsibilities include engaging CISOs and security teams, conducting market and competitive research, analyzing product metrics and feedback, defining and prioritizing features, managing the backlog, and collaborating with engineering, design, marketing, sales, and customer success through launch and adoption.

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.

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.

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.

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.

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.