Senior GenAI Engineer

The Italian Institute of Artificial Intelligence (AI4I) is headquartered in the standout location of OGR, Turin , with the unique mission to support both applied research and on-site deployment of AI . We are established to generate real-world impact at the intersection of science, technology, and industrial transformation.

Research units focus on topics such as secure and trustworthy AI, physical AI and multi-agent systems while the deployment unit is responsible for the implementation at client site. A dedicated high-performance computing center , including next-generation GPU systems such as NVIDIA B200 accelerators, is available to support both research and industrial deployment.

Our System User Knowledge platform and OGR-based network connect corporates, SMEs, startups, and scientific partners, fostering workshops and collaboration with external partners to remain at the forefront of innovation.

Within the Deployment Unit, we are hiring a Senior GenAI Engineer who will operate as a hands‑on tech lead for client projects , owning end‑to‑end architecture, infrastructure, and production deployment of LLM applications. This is a highly hands‑on role for someone who combines strong software engineering skills with deep knowledge of the GenAI ecosystem , including RAG architectures, orchestration frameworks , evaluation methods, and deployment patterns .

You will work closely with:

• Deployment and Data Science team , delivering production‑grade AI services
• Research units , to industrialize promising use cases emerging from applied research
• Industrial and institutional partners , ensuring solutions meet operational, safety, and compliance requirements

• Lead AI delivery (solution architecture, infrastructure decision and deployment) in projects and scope them and their technical feasibility through client interaction.
• Configure foundation models and define prompting + tool‑use strategies for business workflows.
• Evaluate and select the most appropriate AI providers and frameworks based on performance, cost, latency, safety and scalability.
• Define and implement approaches for prompt evaluation, hallucination mitigation, guardrails, observability, and human‑in‑the‑loop review where needed.
• Deploy and operate GenAI services in production integrating LLM APIs, vector databases, orchestration frameworks, backend services, cloud infrastructure, and monitoring.
• Apply agentic AI‑assisted coding to reduce cycle time and improve results across the above responsibilities.

• Master’s degree in Computer Science, Engineering, Physics or related; PhD a plus.
• Strong hands‑on experience (5+ years) building and deploying applications based on deep learning frameworks (e.g., TensorFlow, PyTorch), RAG architectures, task‑specific copilots or multi‑step reasoning systems.
• Strong Python skills and solid experience with agentic AI‑assisted coding (e.g., Claude Code, Codex), modern LLM tooling (e.g., LangChain, LangGraph, ADK) and API integration patterns .
• Solid data foundations : SQL and experience with data warehouses and ETL/ELT pipelines; familiarity with vector databases (e.g., pgvector, Qdrant, Redis).
• Experience with evaluation frameworks : model choice, prompt strategies, retrieval tuning with attention to latency and token/cost usage.
• Production‑grade delivery: Kubernetes + Docker + Git and hands‑on exposure to CI/CD, observability and tracing tools such as OpenTelemetry, Grafana/Prometheus.
• Hands‑on experience in designing cloud enterprise solutions for GenAI workloads (e.g., Azure OpenAI/ Bedrock/ Vertex AI) with at least one hyperscaler stack (Azure/ AWS/ etc.), including deployment, monitoring and cost control.
• Familiarity with multiple AI providers and model ecosystems, including commercial APIs and/or open‑source models.
• Proficiency in Italian and English .

• Experience with fine‑tuning strategies.
• Experience with guardrails , safety tooling, and/or AI compliance (e.g. AI Act, internal AI governance).
• Experience with edge analytics or deployment in constrained industrial environments.
• Broad software engineering background, including experience with at least another programming language (e.g. Java, Typescript, C/C++), NoSQL databases , distributed and cloud‑native systems.
• Knowledge of frontend integration for AI assistants/copilots.

• Access to our advanced computing infrastructure
• A team with engineers and researchers working together on real industrial AI deployments
• Chance to co‑author papers for top‑tier conferences like NeurIPS, ICML, CoRL, and RSS
• Exposure and collaboration with a huge network of corporates, SMEs, startups and technology partners
• An exceptional workplace @OGR, Turin at the epicenter of tech
• Lots of learning opportunities : IAS, internal Academy, budget for events, conferences and online courses
• Relocation incentives and competitive benefits package (including potential tax advantages for international candidates, where applicable)