Top Artificial Intelligence Jobs in Israel

Lead end-to-end AI initiatives for the Customer organization: translate company AI strategy into executable plans, support GTM and launches, design operational processes, define KPIs, analyze performance, and drive cross-functional alignment and communications while building frameworks and executing in ambiguous, fast-paced environments.

Lead a 0-to-1 product area building AI trust for autonomous agents: define strategy, design trust and governance surfaces, run research and experiments, work closely with enterprise customers, and drive cross-functional execution to enable safe, transparent, scalable agent adoption.

Own go-to-market for monday CRM AI: develop and package AI use cases, create high-cadence content, activate sales field with plays and demos, influence product roadmap, build GTM partnerships, and drive AI adoption and revenue.

Lead org-wide adoption of AI across 100+ Product Managers by defining AI-for-Product strategy, launching high-value AI workflows, enabling adoption through playbooks and training, partnering cross-functionally, establishing responsible AI guardrails, and measuring impact to iterate and scale.

Design and build AI-native systems and agent orchestration from 0→1. Own model quality lifecycle, evaluation frameworks, production monitoring, and continuous improvement. Rapidly experiment with models, prompts, and architectures, and collaborate with product and engineering to deploy reliable, scalable AI features.

Lead the global AI go-to-market motion: create sales playbooks, enable sellers and marketers, present AI capabilities to customers, drive adoption and pipeline, and align Product, Enablement, and Marketing around AI positioning.

Lead transformation of BI into an AI-driven data strategy: design and own a governed semantic knowledge layer, implement GenAI solutions and LLM-powered workflows, orchestrate AI agents, ensure data quality, governance, and self-service insights across the company.

Lead development of internal AI-driven developer tools and agents, owning design through deployment. Collaborate with Product and R&D to prototype and build features that improve developer velocity, code quality, and reliability, while mentoring engineers and monitoring productivity metrics for continual optimization.

Lead the developer-focused AI product vision and roadmap, build agentic developer tools and infrastructure, drive adoption through user research and metrics, coordinate cross-organizational initiatives, and ship AI-powered developer workflows and integrations while measuring quality and impact.

Design and build production AI products, agents, and workflows for GTM teams. Own projects end-to-end from discovery to deployment, evaluate emerging AI technologies, develop scalable LLM-based systems and orchestration, partner cross-functionally, and establish engineering best practices to drive measurable business impact.

Support sales by delivering technical demos, POCs, and workshops; translate customer needs into solutions; design integrations, automation, and playbooks; respond to procurement requests; collaborate with sales, product, and support throughout the pre-sales lifecycle.

Design and build AI-driven developer workflows and agents within Datadog, from prototyping to production. Implement prompt engineering, evals, and integrations with developer tools and extensions. Collaborate with product teams to productionize LLM-based features (e.g., debugging agents), iterate with users, and follow LLM/agent research to improve developer productivity.

Build and operate reliable production platforms and AI-integrated services. Improve observability, automate toil, troubleshoot AI provider/API issues, implement IaC, and support on-call incident response tied to SLOs.

The AI Engineer is responsible for designing, implementing, and deploying AI systems and applications, focusing on machine learning models and large language models (LLMs).

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.

The GTM AI Product Manager will execute GTM strategies into operational AI solutions, manage project scopes, and ensure successful implementations across teams, while building prototypes and facilitating stakeholder partnerships.

Lead security architecture, risk assessments, and threat modeling across cloud, SaaS, enterprise, and AI initiatives. Define security requirements, AI security strategy, governance, and vendor/security reviews. Guide compliance, audit readiness, and mentor security teams while influencing technical and executive stakeholders to enable secure adoption of emerging technologies.

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 AI System Architect leads and defines enterprise AI architecture, oversees integration strategies, manages platforms, and ensures governance compliance, shaping the AI roadmap and managing technical standards.

Lead direct sales to government ministries, defense and public safety agencies in Israel. Develop territory strategy, manage complex procurements and tenders, collaborate with engineering to map solutions, cultivate executive relationships, and drive end-to-end pipeline to exceed revenue targets.

Own and evolve monday.com's monetization infrastructure including product catalog, CPQ, license management, usage metering, and consumption-based billing. Define strategy, translate commercial plans into scalable products, partner with pricing and business teams, and drive roadmap execution to support AI-driven pricing and billing at scale.

As a Senior Product Manager, you will define and evolve GitLab's AI Platform Management capabilities, focusing on AI Control Plane and strategic governance. You'll lead product discovery, drive stakeholder alignment, and collaborate across teams to deliver effective management solutions for AI usage.

The Senior AI Engineer will design and maintain AI capabilities, develop internal servers, implement evaluation frameworks, and foster AI practices while collaborating across departments at Riskified.

Partner with Customer Success to identify and deliver AI use cases: build, test, and operationalize AI agents, automations, and workflows integrated with CS systems (Zendesk, Slack, Notion, CRM). Drive adoption through enablement, define KPIs, measure impact, and translate field intelligence into product and process improvements to move CS from reactive support to proactive operational intelligence.

Lead a team of engineers to design and implement scalable systems for AI-driven experiences, ensuring integration across the platform, while fostering a culture of innovation and growth.