We are looking for an AI Hub Tech Lead to join our AI Services and Delivery team. In this role you will have the chance to shape from the ground up the AI Delivery team set up within the local geographies in alignment with group HUB. As Group AI products, we are opening another pole to scale up team size in a different country, and this represents a unique opportunity to shape the AI delivery for Unicredit Group. As AI Hub Tech Lead in Romania, you will oversee insourcing of local talent, held accountability for vertical (business driven) and horizontal (AI Capabilities driven) AI Systems delivery and shape the operating model of the local hub in alignment with central guidelines and standards. In this role you will be both focused on technical and delivery aspects and on people management, overseeing AI resources (data Scientist and AI Engineers) within the local hub.
You will
- Manage local Hub resources in terms of career development, staffing allocation and goals in alignment with central hubs.
- Work jointly with group hub to properly identify staffing allocations for project delivery depending on Business requirements and priorities.
- Foster group-wide collaboration with central AI Hub, building bridges and connection with central AI team guidelines and chapters (Engineering, Data Science).
- Act as Lead for project delivery and escalation point for timeline mismatch and stakeholder expectations alignment.
- Lead Technical squads in day-by-day activities guaranteeing timeline adherence and project objectives realization.
- University degree in computer science, physics, mathematics or engineering.
- 5+ years of practical relevant experience in AI System deliveries, possibly in enterprise environments.
- Experience in managing delivery teams, including focus on people management.
- In-depth knowledge of Software Engineering best practices, design and architectural patterns.
- In-depth knowledge of standard AI methodologies spanning from computer vision to generative AI And agentic AI.
- Hands-on experience with AI systems in production, embedded into enterprise ecosystems.
- Proven experience in application development, leveraging cloud infrastructure, including cloud services usage and integration. (Google preferred, Azure nice to have)
- Eager to learn and stay up to date to AI trends, technologies and framework
- Excellent collaboration skills, with the ability to work effectively in an agile environment.
- Practical experience in using ML and/or AI frameworks (e.g. KubeFlow, Langchain, Haystack, ...)
- Experience and Machine Learning Engineer – MLOps lifecycle for traditional AI systems.
- Experience with Open Source LLMs in production, LLM fine tuning and deployment.
- Experience in testing strategy (unit test, integration test, scalability test) with a focus on AI systems and LLM scalability.
- Experience in designing and developing microservices architecture.
- Knowledge of DevOps best practices, with proven experience of deployments on Kubernetes.
- Experience in object-oriented software development in Python, knowledge of APIs design and implementation - additional languages are a plus.
- Practical knowledge of Kubernetes and Docker.
- Experience with Agentic AI system design, development and maintenance in an enterprise setting with production grade infrastructure.
