Technical Program Manager

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. 

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.  

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. 

We are looking for a Senior Technical Program Manager to join our Life Sciences R&D product team and support the digital transformation of a leading pharmaceutical company.

In this role, you will lead strategic technical programs and portfolios of applications supporting researchers, cell biologists, computational biologists, and data scientists. You will work across product, engineering, data, AI/ML, and scientific teams, translating complex scientific needs into scalable technical solutions and driving delivery from discovery and requirements through launch.

The role combines strategic program management, product and backlog ownership, technical understanding of cloud and data platforms, and strong knowledge of human biology and life sciences.

You will:

• own and prioritize product backlogs across multiple technical workstreams, including human biological data repositories, analytical pipelines, and search and visualization platforms,
• lead strategic programs through product development lifecycle governance, from strategy and requirements validation through architecture review and launch,
• translate complex scientific and business requirements into clear user stories, acceptance criteria, product development plans, and actionable technical requirements,
• coordinate dependencies across data engineering, platform engineering, UI/UX, AI/ML, and scientific knowledge engineering teams,
• drive continuous discovery, user research, and feedback loops with scientists and R&D stakeholders to shape product roadmaps,
• define and maintain data models, metadata standards, FAIR data requirements, and data governance practices together with scientific and data teams,
• ensure security, compliance, data provenance, and traceability requirements are addressed throughout the product lifecycle,