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.

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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)

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