Senior AI Engineer

msg Group

Monza

Presencial

EUR 55 000 - 65 000

Tempo integral

há 35 horas
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Resumo da oferta

msg Group is seeking a seasoned software engineer to translate business processes into AI agents and reliable production systems in Lombardy, Italy. You will design end-to-end pipelines, select tools, and manage human handoffs to ensure accuracy and trust in deployed models.

This role focuses on scalable retrieval, grounding, and evaluation capabilities, balancing model quality with cost and latency while collaborating with business experts to translate domain logic into testable artifacts.

Qualificações

  • 5+ years software development experience, 2+ years with production LLM-based systems
  • Strong Python fundamentals: version control, tests, code reviews, incremental delivery
  • Experience with async work, FastAPI and Pydantic or equivalents
  • Hands-on with at least one agent orchestration framework (LangGraph, LlamaIndex Workflows, OpenAI Agents SDK, Temporal)
  • Experience serving models via managed platforms (AWS Bedrock, Azure AI Foundry, Google Vertex AI) or provider APIs with streaming, structured output, prompt caching, rate-limiting
  • Production vector search experience (pgvector, Qdrant, Pinecone, Weaviate, Milvus, Azure AI Search) with understanding of trade-offs
  • Deep retrieval expertise (chunking, metadata filtering, query rewriting, hybrid search, reranking)
  • Fluent in tool and function calling, structured output, and multi-step agent design
  • Hands-on with Model Context Protocol (MCP): building servers, tool interfaces, auth and error handling
  • Evidence of a solid evaluation discipline and a measurable eval harness
  • Ability to work with business experts to produce workable specifications
  • Judgment to select appropriate tools vs rules engines and plain queries
  • Fluent English

Responsabilidades

  • Decompose business processes into steps, tools, handoffs, and decision points for agent-based execution
  • Design and implement retrieval pipelines with chunking, embedding models, hybrid search, and grounding to source data
  • Treat prompt and context engineering as an engineering discipline with versioning, tests, and measurement
  • Build the evaluation layer with datasets, automated scoring, and regression suites
  • Instrument production systems for observability: traces, latency, costs, failure rates, and drift
  • Own end-to-end quality and diagnose failures to their root cause across retrieval, reasoning, tooling, or data
  • Balance model quality, cost, and latency, adapting choices as models evolve
  • Collaborate with business experts to extract domain logic and translate it into testable artifacts
  • Take agents into production with platform and infrastructure teams and monitor live behavior

Conhecimentos

Python
Async programming
Communication with stakeholders
English fluency

Ferramentas

FastAPI
Pydantic
LangGraph
LlamaIndex Workflows
OpenAI Agents SDK
Temporal
AWS Bedrock
Azure AI Foundry
Google Vertex AI
pgvector
Qdrant
Pinecone
Weaviate
Milvus

Descrição da oferta de emprego

Overview

As part of the msg group, you will translate business processes into reliable, production-ready AI agents and systems. You design end-to-end pipelines, selection of tools, and human handoffs to ensure accuracy and trust in deployed models. You focus on turning complex domain logic into testable, measurable solutions with clear ownership of quality. This role combines engineering rigor with business impact, delivering scalable retrieval, grounding, and evaluation capabilities. A meaningful chance to shape how AI touches real work for leading enterprises.

Retribuzione / Benefits
  • competitive salaries 55.000 - 65.000 Eur
  • broad range of benefits
  • diversity and cultural differences are cherished
Responsabilità
  • Decompose business processes into steps, tools, handoffs, and decision points for agent-based execution
  • Design and implement retrieval pipelines with chunking, embedding models, hybrid search, and grounding to source data
  • Treat prompt and context engineering as an engineering discipline with versioning, tests, and measurement
  • Build the evaluation layer with datasets, automated scoring, and regression suites
  • Instrument production systems for observability: traces, latency, costs, failure rates, and drift
  • Own end-to-end quality and diagnose failures to their root cause across retrieval, reasoning, tooling, or data
  • Balance model quality, cost, and latency, adapting choices as models evolve
  • Collaborate with business experts to extract domain logic and translate it into testable artifacts
  • Take agents into production with platform and infrastructure teams and monitor live behavior
Requisiti fondamentali
  • 5+ years software development experience, 2+ years with production LLM-based systems
  • Strong Python fundamentals: version control, tests, code reviews, incremental delivery
  • Experience with async work, FastAPI and Pydantic or equivalents
  • Hands-on with at least one agent orchestration framework (LangGraph, LlamaIndex Workflows, OpenAI Agents SDK, Temporal)
  • Experience serving models via managed platforms (AWS Bedrock, Azure AI Foundry, Google Vertex AI) or provider APIs with streaming, structured output, prompt caching, rate-limiting
  • Production vector search experience (pgvector, Qdrant, Pinecone, Weaviate, Milvus, Azure AI Search) with understanding of trade-offs
  • Deep retrieval expertise (chunking, metadata filtering, query rewriting, hybrid search, reranking)
  • Fluent in tool and function calling, structured output, and multi-step agent design
  • Hands-on with Model Context Protocol (MCP): building servers, tool interfaces, auth and error handling
  • Evidence of a solid evaluation discipline and a measurable eval harness
  • Ability to work with business experts to produce workable specifications
  • Judgment to select appropriate tools vs rules engines and plain queries
  • Fluent English
  • comfort with ambiguity
  • strong communication with business stakeholders
  • collaboration across cross-functional teams
  • Python
  • FastAPI
  • Pydantic
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