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AI and Machine Learning Software Engineer
On-siteFull-timeAI & Machine LearningElectronics ManufacturingData Infrastructure
Join an enterprise AI platform team in Israel to build governed agentic tooling and distributed services for AI-assisted engineering workflows across hybrid on-premises and cloud environments.
Responsibilities
- Build and extend an agentic command-line harness, including skills, tool definitions, context and memory management, sandboxing, and execution controls.
- Design and implement gateway integrations, session and state management, job execution, caching, and secure connections to on-premises services.
- Develop MCP servers, skills, and integrations for engineering data and tools.
- Apply practical knowledge of LLM behavior, prompt and skill design, token costs, failure modes, and evaluation to improve agent reliability.
- Add tracing, metrics, and evaluation pipelines; debug behavior across CLI, gateway, and model layers.
- Write maintainable, well-tested code and create automated tests and agent evaluation suites.
- Participate in incident response, postmortems, code reviews, and design reviews.
- Gather requirements from teams adopting the platform, support early users, and contribute feedback to the roadmap.
- Track developments in agent frameworks, coding agents, MCP, and AI infrastructure.
Requirements
- Bachelor’s degree in computer science, software engineering, artificial intelligence, or a related field.
- Two to three years of professional experience building and operating backend or distributed systems in production.
- Strong Python skills and working knowledge of TypeScript or JavaScript.
- Experience designing services, REST or GraphQL APIs, asynchronous systems, event-driven systems, and reliable client-server communication.
- Practical understanding of LLM APIs, tool calling, context and memory management, retrieval-augmented generation, embeddings, and evaluation.
- Experience with or demonstrated interest in agentic frameworks and protocols such as LangGraph, LangChain, and MCP.
- Experience with Docker and containerized deployments, plus exposure to Kubernetes and hybrid on-premises and cloud environments.
- Working knowledge of PostgreSQL, Redis or Valkey, and vector databases.
- Familiarity with OAuth, OIDC, SSO, secrets handling, Linux, Git, and CI/CD.
- Ability to work collaboratively with distributed engineering teams.
Nice to have
- Experience extending AI coding agents or agentic command-line tools with custom tools, skills, hooks, or MCP servers.
- Familiarity with Go, Rust, Java, or C++.
- Exposure to embedded, firmware, storage systems, lab automation, or hardware-in-the-loop testing.
- Open-source contributions or projects involving AI agents.
- Experience with LLM observability and evaluation tools such as OpenTelemetry, Langfuse, or Grafana.
- Clear written communication and experience working across time zones with distributed teams.
Benefits
- Inclusive workplace focused on diversity, belonging, respect, and contribution.
- Accessibility support is available throughout the application and hiring process.