Product Owner, Agentic Platform & Enterprise Interfaces

Description

The company's scientists and clinicians increasingly use agentic AI platforms and enterprise AI assistants, and the tools only help when the layer around them works. That layer covers the skills people can use, the connectors that give governed access to company data, and how people are onboarded, supported and measured.

You will be the day-to-day product owner for the agentic platform used in R&D for as long as it runs. You will own the skills library, marketplace and data connectors, keep data access governed, keep costs and usage visible, and make sure users are onboarded and supported well. As the platform landscape changes, you will keep the user experience and governance consistent.

You will work with AI scientists and engineers, enterprise AI platform and gateway teams, information security, architecture, data owners and external delivery partners. The work is hands-on and moves quickly, so you need to be comfortable with technical detail, able to decline requests clearly, and care about how users experience the product.

Responsibilities

• Own the roadmap, backlog and release priorities for the R&D agentic platform and its interfaces, and agree scope and sequencing with engineering leads.
• Decide which capabilities the platform should provide itself and which should move to enterprise assistants as those mature.
• Write clear product requirements, acceptance criteria and release notes, and keep a record of decisions.
• Own the skills library and marketplace from intake through quality review, publication, retirement and ownership of each skill.
• Own the connector roadmap, including connectors to enterprise data and systems built on open standards such as the Model Context Protocol (MCP). Rank requests by value, risk and engineering capacity.
• Set the criteria for approving connectors and skills, and work with security, architecture and data owners so each one is reviewed before release.
• Define with data owners and security how users get data access through the platform, including approval flows and criteria for patient-related data.
• Track security findings, such as weaknesses in how credentials, secrets or conversations are handled, until they are closed.
• Keep access, audit and retention requirements visible in the backlog, and review them with Product Compliance.
• Run intake and onboarding for new users and groups, including seat allocation and the weekly review of access requests.
• Work with support engineers and change partners on support queues, user communications and training.
• Respond to business area requests already in progress, giving each a clear answer and timeline.
• Own the platform's usage and cost metrics, including model and token cost per session, and work with finance and platform teams on budgets and tiers.
• Define and report value measures and user stories that show what the platform delivers in R&D.
• Bring a clear view of run cost and options into planning cycles.
• Work closely with AI scientists, engineers, enterprise AI gateway and platform teams, security, architecture and business sponsors.
• Explain clearly what is shipping, what is blocked and why, including when a request has to wait.

Requirements

• Five or more years as a product owner or product manager of a technical platform, data platform, API or developer-facing product.
• Experience with LLM-based applications or agentic systems, including how skills, tools and connectors are managed.
• Working knowledge of APIs and integration patterns, and ideally of the Model Context Protocol (MCP).
• Experience managing user access, onboarding and support for an enterprise tool.
• Understanding of information security and data access governance, ideally in a regulated environment.
• Experience tracking usage and cost for cloud or AI services and making product decisions from that data.
• A proven ability to prioritise a long queue of requests and explain trade-offs clearly.
• Desirable: experience in pharmaceutical or life sciences R&D.
• Desirable: familiarity with FinOps practices for cloud or model usage.
• Desirable: working knowledge of Atlassian tools (JIRA, Confluence).

Conditions

In-office role based in Barcelona, Spain.

You must work on-site at least three days per week.

Remote working and travel flexibility are not available.

Posted 26-oct-2026. Closing date 08-nov-2026.

Posting code: EAI.

The company is committed to equal opportunity and complies with applicable laws on non-discrimination, work authorization and employment eligibility verification.