Требования: To be successful in this role you have: 7+ years building production software systems with a strong track record on reliability, performance, and scalability Hands-on experience shipping generative AI products — not just integrating LLM APIs or building prototypes, but owning AI-powered features that production users depend on Solid depth in how large language models work: failure modes, context constraints, and how prompt design shapes model behavior at scale Python, Kubeflow,Experience with SageMaker, Vertex AI or AzureML, SQL Practical prompt engineering experience: systematically designing, versioning, and evaluating prompts across model updates or A/B evaluation cycles A real track record in eval engineering — not just familiarity, but a portfolio of evaluation suites designed, shipped, and used to drive quality decisions in production AI systems Cost and efficiency awareness at the system level: experience reasoning about model routing, inference cost, and latency tradeoffs in production Strong software engineering fundamentals: distributed systems, API design, and testing discipline Comfort operating in fast-moving, ambiguous, startup-like AI product environments Nice to Have Experience with multi-agent coordination patterns (A2A, MCP) Familiarity with agent frameworks (LangChain, Llama
Index, or similar) Prior experience shipping AI systems in enterprise software Experience with AI observability tooling (tracing, cost tracking, LLM-specific monitoring) Fami