Senior GenAI Engineer

• Scope : Tech Lead / Forward Deployed Engineer for LLM + agentic architecture, infrastructure, and deployment
• Salary range : €70,000 – €90,000 gross/year (depending on experience)

About AI4I and our culture

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.

Role Summary

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

What you will do

• 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.

About you

• 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 .

Nice to Have

• 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.

We encourage you to apply even if you do not believe you meet every single qualification . Not all strong candidates will meet every single qualification as listed.

What we offer

• 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)

Selection process

• Fit interview
• Technical live assessment
• Final motivation interview

How to apply

Submit your application exclusively through the online form including:

• CV
• Cover letter (max. 1 page) describing how your profile fits the position and personal projects , if any
• Optional, links to code repositories (e.g., GitHub), personal webpage or projects (e.g., open‑source contributions)
• Optional, names of two references

Note: to ensure a timely process, we will only be in touch with candidates who progress to the interview stage.