Senior AI Engineer
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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
- 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
- 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
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