Overview In this role you will architect and operationalize production-grade AI systems that transform business processes. You'll translate domain knowledge from business experts into reliable agents, pipelines, and evaluation frameworks. You work closely with cross-functional teams to ensure accuracy, efficiency, and governance of AI solutions in real work. You enable scalable, end-to-end AI capabilities that businesses can trust and adopt, driving measurable impact. Retribuzione / Benefits broad range of benefits Decompose business processes into agent-driven workflows and define steps, tools, handoffs, and human-in-the-loop decision points Design and build retrieval pipelines (chunking, indexing, embedding selection, hybrid search, reranking, grounding) Treat prompt/context engineering as an engineering discipline with versioning and tests Build and maintain evaluation layers (golden datasets, automated scoring, model-graded evals, regression tests) Instrument production systems for observability (traces, token cost, latency, failure rates, data/model drift) Own end-to-end quality and diagnose failures by tracing issues to retrieval, reasoning, tool design, or data Choose and manage model trade-offs between quality, cost,



and latency as models evolve Collaborate with business experts to extract domain logic and turn it into testable artifacts Take agents to production with infrastructure teams and ensure responsible live behavior 5+ years of software development experience ~2+ years with production-ready LLM-based systems ~ Strong Python skills and standard engineering practices ~ Experience with async, FastAPI, Pydantic ~ Experience serving models via managed platforms (AWS Bedrock, Azure AI Foundry, Google Vertex AI) or provider APIs ~ Production vector search experience (pgvector, Qdrant, Pinecone, Weaviate, Milvus, Azure AI Search) ~ Deep retrieval knowledge (chunking, metadata filtering, query rewriting, hybrid search, reranking) ~ Fluency with tool/function calling, structured output, multi-step agent design ~ Hands-on with MCP (Model Context Protocol): servers, tool interfaces, authentication, permissions, error handling ~ Experience with evaluation tooling (Langfuse, LangSmith, Phoenix; Ability to work in ambiguity and extract requirements with business experts ~ Fluent English ~ collaboration with cross-functional teams ~ Python ~ FastAPI ~

📌 Senior AI Engineer (Italia)
🏢 Msg Global
📍 Italia