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
competitive salary
broad range of benefits
Responsabilità
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
Requisiti fondamentali
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
Hands-on with agent orchestration frameworks (LangGraph, LlamaIndex Workflows, OpenAI Agents SDK, Temporal)
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; regression suites)
Ability to work in ambiguity and extract requirements with business experts
Fluent English
collaboration with cross-functional teams
strong problem-solving and analytical thinking
clear communication of technical concepts to non-technical stakeholders
Python
FastAPI
Pydantic

📌 Senior Ai Engineer (Monza)
🏢 Msg Global
📍 Monza