Lead Ai Engineer
Descrizione dell'offerta
For our client, international strategy company leader in SAAS applications, we are looking for an:
Senior AI Engineer
The resource will lead the design and implementation of the Co-Pilot's orchestration layer - the intelligent backbone that powers the multi-agent reasoning system. The candidate will be the technical architect who translates the ambitious product vision into a scalable, production-ready AI infrastructure.
Responsabilità
Key Responsibilities Architecture & System Design (40%)
- Design and implement the AIAgent Orchestrator using LangGraph/LangChain and the Model Context Protocol(MCP).
- Architect a stateful workflowsystem to manage document processing, agent lifecycles, and human-in-the-loopinteractions.
- Define agent communicationprotocols, JSON-based data schemas, and the lifecycle management framework.
- Build an Agent Registry forversioning, discovery, and dynamic routing of specialized agents.
- Design fault-tolerant workflowswith retries, fallbacks, partial-result preservation, and rollback mechanisms.
- Create a multi-model routinglayer to balance latency, cost, and accuracy across GPT, Claude, Gemini, andopen-source models.
Implementation & Development (30%)
- Build the Agent Executor tomanage reasoning loops, retrievals, and validation tasks.
- Develop core System Agents(e.G., Query Understanding, Context Retrieval, Reasoning, Memory, Validation).
- Implement an asynchronousexecution framework using RabbitMQ/Kafka/SQS for long-running workflows.
- Create prompt management toolsfor versioning, A/B tests, and regression testing.
- Develop observability pipelineswith OpenTelemetry, LangSmith, and custom telemetry for tracing agent activity.
Integration & Collaboration (20%)
- Partner with the KnowledgeGraph Engineer to combine vector search and graph-based reasoning
- Work with Data Scientists toembed their prompts and reasoning chains into the orchestration layer.
- Collaborate with frontendengineers to design WebSocket and REST APIs for real-time agent interactions.
- Integrate with backend servicesfor ETL pipelines, validation utilities, and memory/session management.
Leadership & Strategy (10%)
- · Lead design and architecturereviews for the AI services layer.
- Evaluate and adopt emerging AIframeworks, models, and tools.
- Define code standards, testingpractices, and documentation guidelines for multi-agent systems.
- Contribute to roadmap andsprint planning, aligning product vision with delivery milestones.
- Mentor AI engineers and supporttheir technical growth.
Profilo
Experience & Background
- 8+ years in software engineering, AI/ML engineering, or related fields
- 3+ years working with LLMs, multi-agent systems, or agentic AI architectures
- Proven track record of architecting and shipping production AI systems at scale
- Experience leading technical projects or small engineering teams
Technical Skills
- Expert-level Python with strong async/await patterns and type hints
- Deep experience with LangChain, LangGraph, or similar agent orchestration frameworks
- Production experience with LLM APIs (OpenAI, Anthropic, Google) and understanding of prompt engineering, temperature/token controls, and cost optimization
- FastAPI or similar async web framework experience
- Hands-on experience with vector databases (Weaviate, Pinecone, FAISS, Chroma) and semantic search
- Familiarity with graph databases (Neo4j, TigerGraph) and query languages (Cypher, SPARQL)
«I candidati, nel rispetto del D.Lgs. 198/2006, D.Lgs. 215/2003 e D.Lgs. 216/2003, sono invitati a leggere l'informativa sulla privacy consultabile sotto il form di richiesta dati della pagina di candidatura (Regolamento UE n. 2016/679).
L'offerta è rivolta a candidati di entrambi i sessi, nel rispetto del D.Lgs. 198/2006 e della normativa vigente in materia di pari opportunità. L'azienda promuove un ambiente di lavoro inclusivo e garantisce pari opportunità a tutte le persone, indipendentemente da genere, età, origine, orientamento sessuale o disabilità.»
Senior AI Engineer
The resource will lead the design and implementation of the Co-Pilot's orchestration layer - the intelligent backbone that powers the multi-agent reasoning system. The candidate will be the technical architect who translates the ambitious product vision into a scalable, production-ready AI infrastructure.
Responsabilità
Key Responsibilities Architecture & System Design (40%)
- Design and implement the AIAgent Orchestrator using LangGraph/LangChain and the Model Context Protocol(MCP).
- Architect a stateful workflowsystem to manage document processing, agent lifecycles, and human-in-the-loopinteractions.
- Define agent communicationprotocols, JSON-based data schemas, and the lifecycle management framework.
- Build an Agent Registry forversioning, discovery, and dynamic routing of specialized agents.
- Design fault-tolerant workflowswith retries, fallbacks, partial-result preservation, and rollback mechanisms.
- Create a multi-model routinglayer to balance latency, cost, and accuracy across GPT, Claude, Gemini, andopen-source models.
Implementation & Development (30%)
- Build the Agent Executor tomanage reasoning loops, retrievals, and validation tasks.
- Develop core System Agents(e.G., Query Understanding, Context Retrieval, Reasoning, Memory, Validation).
- Implement an asynchronousexecution framework using RabbitMQ/Kafka/SQS for long-running workflows.
- Create prompt management toolsfor versioning, A/B tests, and regression testing.
- Develop observability pipelineswith OpenTelemetry, LangSmith, and custom telemetry for tracing agent activity.
Integration & Collaboration (20%)
- Partner with the KnowledgeGraph Engineer to combine vector search and graph-based reasoning
- Work with Data Scientists toembed their prompts and reasoning chains into the orchestration layer.
- Collaborate with frontendengineers to design WebSocket and REST APIs for real-time agent interactions.
- Integrate with backend servicesfor ETL pipelines, validation utilities, and memory/session management.
Leadership & Strategy (10%)
- · Lead design and architecturereviews for the AI services layer.
- Evaluate and adopt emerging AIframeworks, models, and tools.
- Define code standards, testingpractices, and documentation guidelines for multi-agent systems.
- Contribute to roadmap andsprint planning, aligning product vision with delivery milestones.
- Mentor AI engineers and supporttheir technical growth.
Profilo
Experience & Background
- 8+ years in software engineering, AI/ML engineering, or related fields
- 3+ years working with LLMs, multi-agent systems, or agentic AI architectures
- Proven track record of architecting and shipping production AI systems at scale
- Experience leading technical projects or small engineering teams
Technical Skills
- Expert-level Python with strong async/await patterns and type hints
- Deep experience with LangChain, LangGraph, or similar agent orchestration frameworks
- Production experience with LLM APIs (OpenAI, Anthropic, Google) and understanding of prompt engineering, temperature/token controls, and cost optimization
- FastAPI or similar async web framework experience
- Hands-on experience with vector databases (Weaviate, Pinecone, FAISS, Chroma) and semantic search
- Familiarity with graph databases (Neo4j, TigerGraph) and query languages (Cypher, SPARQL)
«I candidati, nel rispetto del D.Lgs. 198/2006, D.Lgs. 215/2003 e D.Lgs. 216/2003, sono invitati a leggere l'informativa sulla privacy consultabile sotto il form di richiesta dati della pagina di candidatura (Regolamento UE n. 2016/679).
L'offerta è rivolta a candidati di entrambi i sessi, nel rispetto del D.Lgs. 198/2006 e della normativa vigente in materia di pari opportunità. L'azienda promuove un ambiente di lavoro inclusivo e garantisce pari opportunità a tutte le persone, indipendentemente da genere, età, origine, orientamento sessuale o disabilità.»