Agentic AI Engineer (Engineering, Web&Mobile Team)

As an Agentic AI Engineer, you will build AI-powered workflows that accelerate engineering teams and improve developer productivity. You will orchestrate LLMs and AI agents into reliable, production-grade tooling that operates at scale. The role requires strong software engineering/ architecture expertise, combined with a product mindset and the ability to adapt quickly in the rapidly evolving agentic AI landscape.

What you’ll have to do:

Design and ship agentic workflows across the dev lifecycle — auto-documentation, test generation on MRs, parity testing for migrations, review augmentation;

Build reusable platform components: MCP servers, tool integrations, prompt/ orchestration libraries other teams can self-serve;

Own eval & observability for AI flows (Langfuse, LLM-as-judge, regression suites) so outputs are trustworthy, not just impressive demos;

Deploy flows as production services (Docker, K8s) with proper CI/CD and cost/ latency awareness;

Drive adoption at scale — measure impact via developer-productivity metrics (e.g. getDX), iterate on what actually moves throughput and cycle time;

Keep pace with and adapt to the fast-moving agentic landscape — continuously evaluate new tools, models, and patterns, fold the useful ones into how the org works, and bring pragmatic choices.

What makes you a good fit:

Strong programming fundamentals and a track record shipping production-grade software (Python is the primary language of the agentic ecosystem);

Hands-on with agentic coding tools (Claude Code, Cursor, Aider, Copilot) and having built at least one real agentic flow in production;

Working knowledge of LLM tool calling and MCP (Model Context Protocol);

Experience with one or more orchestration frameworks (LangGraph, LangChain, or equivalent custom orchestration on LLM provider APIs);

Comfortable with cloud, Docker, and Kubernetes;