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Senior AI Engineer, AI Platform
·Israel
Not specifiedFull-timeAI EngineeringMental Health Care
Join an AI Platform team building production systems that improve the software development lifecycle. Own measurable outcomes, discover automation opportunities, and develop reliable agentic workflows and platform infrastructure.
Responsibilities
- Own team KPIs and determine which initiatives will improve them
- Engage engineering teams to identify inefficient or manual software development lifecycle processes
- Design, build, and ship agentic workflows from prototype through production
- Develop and manage agent context, knowledge, and scaffolding across agent harnesses
- Build evaluations, checks, and feedback loops to improve agent reliability
- Extend the AI platform, including agents, integrations, and runtime infrastructure
- Prioritize work based on measurable impact rather than a predefined ticket queue
- Demonstrate the impact of delivered systems on team KPIs
- Collaborate with engineers to maintain platform coherence as it scales
Requirements
- 6–8+ years of hands-on senior software engineering experience
- Production experience building and shipping agentic workflows or LLM-powered systems
- Experience with agent harnesses and managing agent context, knowledge, and scaffolding at scale
- Practical knowledge of LLMs, retrieval-augmented generation, tool use, evaluations, and human-in-the-loop patterns
- Ability to design, build, and operate systems end to end
- Ability to discover problems, scope solutions, and work from goals or KPIs without a predefined specification
- Strong product judgment and ability to measure whether solutions deliver impact
- Strong discovery and communication skills
Nice to have
- Experience with Kubernetes, containers, or CI/CD infrastructure in production
- Experience with MCP-based tooling, agent orchestration frameworks, or LLM gateways
- Familiarity with observability tools such as Datadog
- Experience in a fast-paced, high-growth B2B SaaS environment
- Exposure to health technology, healthcare institutions, or behavioral health
- Cost-aware approach to managing model tokens