Senior AI Engineer

Job Summary

As a Senior AI Engineer, you will design, build, and govern production-grade Generative AI and Retrieval-Augmented Generation (RAG) systems for internal use across Global V&V & R&D, engineering, analytics, and knowledge-intensive functions. This is systems engineering and applied AI role, not research and not prompt-only.

Context:

• Operate under EU regulations (GDPR, data residency, AI Act readiness)
• Comply with Enterprise IT standards (security, auditability, lifecycle)
• Collaborate with Legal, IT Security, Data Protection Officers, Works Council

Objectives & Responsibilities

Architecture Ownership

• Own end-to-end GenAI architecture for internal use cases
• Define RAG reference architectures, embedding/retrieval strategies, model selection guidelines
• Make build vs. buy recommendations with clear trade-offs

Enterprise-Grade RAG Systems

• Design multi-source RAG pipelines (structured + unstructured data)
• Implement advanced retrieval patterns (hybrid search, reranking, context compression)
• Address enterprise failure modes (stale knowledge, conflicting sources, access control)

Evaluation, Risk & Governance

• Define KPIs (precision/recall, grounded Ness, hallucination rate)
• Implement evaluation pipelines and AI Act–aligned transparency artifacts
• Guardrails for PII leakage, prompt injection, data exfiltration

Engineering & Integration

• Build production services (APIs, batch jobs, internal tools)
• Integrate GenAI into data platforms, analytics workflows, developer tooling
• Ensure logging, observability, cost monitoring, feedback loops

Technical Leadership

• Act as technical authority for GenAI internally
• Mentor engineers and data scientists
• Educate stakeholders on GenAI capabilities and limitations

Requirements & Qualifications

• Software Engineering: Strong Python, CI/CD, enterprise SDLC
• GenAI & RAG Expertise: Hands-on experience beyond demos, embeddings, retrieval tuning
• Data & Infrastructure: Vector DBs, SQL, object storage, containerized deployments
• Security & Compliance: GDPR, data residency, RBAC, collaboration with Legal/DPO
• Experience: 5–8+ years in software/ML engineering, 2+ years in GenAI/NLP systems

Preferred Qualifications

Behavioral Criteria

• Think in systems, not prompts
• Communicate risks clearly to non-technical stakeholders
• Balance innovation with stability
• Comfortable with ambiguity

Location

Trieste/Cagliari or remote