Senior Product Owner (AI Build & Delivery Pod - Financial Services) | Lead

Description

We are seeking an experienced Product Owner to join the project of our Client, a leading European financial market infrastructure provider operating exchanges, securities services, and banking operations across Switzerland and Spain. In this role, you will be the single accountable voice for an AI Build & Delivery pod — taking a validated, build-ready AI prototype (complete with quantified value case and guardrail clearance) and industrializing it into a production solution within weeks. You'll own the backlog against the value case, define acceptance criteria for AI features alongside engineers, run embedded business SMEs and senior stakeholders, and steer governance with Compliance, Risk, and Legal from sprint one through to a living-solution handover. This position offers a flex-hybrid model of work, with 3 days per week working from the office located in Warsaw. Responsibilities Own the handover of the build-ready pack with zero re-discovery, resolving any gaps within days rather than re-litigating requirements Own the backlog and prioritization, using the quantified value case as the sole sorting function for every item Define acceptance criteria for AI features together with engineers — eval sets, quality thresholds, guardrail behavior, and escalation paths Run stakeholder and SME engagement so decisions come back in days, not committee cycles Steer governance to production by engaging Compliance, Risk, and Legal continuously from sprint one Prepare the living-solution handover to the Enablement team and the business, clarifying what changes and what it replaces Run hypercare and iteration based on real usage data, deciding fix vs. feature vs. stop on evidence Requirements Proven track record shipping AI or data products to production, with named examples of the value delivered and how quality was measured End-to-end product ownership experience in agile delivery, including senior stakeholder management Business-case fluency — comfortable framing and defending outcomes in hours-freed and cost terms Backlog craft for AI products, treating evals, guardrails, and human-in-the-loop trade-offs as first-class backlog items Hands-on daily use of AI tools to run your own workflow — backlog analysis, stakeholder summaries, draft specs Delivery experience in a regulated industry, with working knowledge of risk, compliance, and data classification requirements Strong English communication skills Nice to have Familiarity with Azure AI Foundry / Azure OpenAI, agentic frameworks, vector databases, knowledge graphs, or MCP Exposure to Python, Java Spring Boot, TypeScript/Angular, or Databricks/Apache Spark environments Background in banking, insurance, or capital markets delivery

Requirements

• Proven track record shipping AI or data products to production, with named examples of the value delivered and how quality was measured

• End-to-end product ownership experience in agile delivery, including senior stakeholder management

• Business-case fluency — comfortable framing and defending outcomes in hours-freed and cost terms

• Backlog craft for AI products, treating evals, guardrails, and human-in-the-loop trade-offs as first-class backlog items

• Hands-on daily use of AI tools to run your own workflow — backlog analysis, stakeholder summaries, draft specs

• Delivery experience in a regulated industry, with working knowledge of risk, compliance, and data classification requirements

• Strong English communication skills

Responsibilities

• Own the handover of the build-ready pack with zero re-discovery, resolving any gaps within days rather than re-litigating requirements

• Own the backlog and prioritization, using the quantified value case as the sole sorting function for every item

• Define acceptance criteria for AI features together with engineers — eval sets, quality thresholds, guardrail behavior, and escalation paths

• Run stakeholder and SME engagement so decisions come back in days, not committee cycles

• Steer governance to production by engaging Compliance, Risk, and Legal continuously from sprint one

• Prepare the living-solution handover to the Enablement team and the business, clarifying what changes and what it replaces

• Run hypercare and iteration based on real usage data, deciding fix vs. feature vs. stop on evidence

Seniority

• Lead

Nice to have

• Familiarity with Azure AI Foundry / Azure OpenAI, agentic frameworks, vector databases, knowledge graphs, or MCP

• Exposure to Python, Java Spring Boot, TypeScript/Angular, or Databricks/Apache Spark environments

• Background in banking, insurance, or capital markets delivery