AI Engineering jobs in Israel

Design and develop production-grade Generative AI solutions for large-scale enterprise environments, including LLM applications, RAG architectures, AI agents, and integrations with business systems.

Lead and build a new engineering team focused on AI agents and intelligent workflows for enterprise data platforms. Define technical direction, develop initial solutions, recruit engineers, and bring AI capabilities into production.

Join a GenAI infrastructure team building reliable AI agents, RAG pipelines, tool-calling workflows, backend services, and reusable platforms for customer-facing industrial AI products.

A senior individual contributor will design, build, and operate AI-powered tools and autonomous agentic workflows for engineering teams. The role covers backend development, API integrations, workflow automation, simple user interfaces, and rapid delivery of reusable internal solutions. It is based在

Design, train, and optimize conversational AI workflows that resolve customer issues, reduce support volume, and improve the customer journey. Collaborate with customer experience, product, technology, and vendor stakeholders in a digital-first environment.

Develop production software, data pipelines, and runtime systems that deploy deep learning models on resource-constrained edge devices.

Build and operate the internal AI and automation infrastructure that supports teams across a global creative technology company. Own platform reliability, identity controls, cloud infrastructure, CI/CD, security, cost management, and safe deployment of AI assistants and workflows.

Join an identity security company’s AI Engineering team to build the platform and production features powering AI-driven access protection. Own systems from research and prototyping through architecture, evaluation, deployment, and ongoing reliability improvements.

Lead the architecture, governance, security, and production integration of AI agents and LLM-based workflows across enterprise platforms in Tel Aviv.

Build and evolve infrastructure for benchmarking, evaluating, and deploying foundation and multimodal AI models. Partner with AI and data science teams to support rigorous, reproducible model development in a hybrid Ramat Gan role.