About Invesco

As one of the world’s leading independent global investment firms, Invesco is dedicated to rethinking possibilities for our clients. By delivering the combined power of our distinctive investment management capabilities, we provide a wide range of investment strategies and vehicles to our clients around the world. If you're looking for challenging work, intelligent colleagues, and exposure across a global footprint, come explore your potential at Invesco.

Your Role

Invesco is expanding its Microsoft Copilot Studio platform to support agent based AI capabilities across the Asset Management value chain. As part of this expansion, we are establishing Technical Product Owners (TPOs) who will own AI agents and capabilities from concept through production and scale.

This role is accountable for ensuring Copilot Studio agents deliver measurable business value, are built to enterprise standards, and scale responsibly across a large developer community.

You will be Responsibilities For:

• Serve as the single accountable owner for a portfolio of Copilot Studio agents, capabilities, or agent families aligned to Invesco domains (e.g., Investments, Research, Product Information, Client Reporting, Operations, Risk & Compliance).

• Define and communicate clear product vision, scope, and success metrics.

• Own the full lifecycle of agents from ideation and MVP through production deployment and ongoing enhancement.

• Act as a trusted partner to business stakeholders across Investments, Distribution, Operations, Risk, Compliance, and Technology Domain Owners.

• Translate asset management workflows and pain points into well‑defined user stories, agent behaviors, and functional requirements.

• Balance business ambition with practical constraints related to data, risk, and platform maturity.

• Own the functional and technical definition of Copilot Studio agents in partnership with developers and platform teams.

• Define agent instructions, guardrails, tone, and response constraints appropriate for financial services use.

• Guide decisions on data sourcing, integrations, APIs, and reuse of components to ensure scalability, reusability, testing, and maintainability.

• Demonstrate a solid understanding of large language model (LLM) fundamentals, including system prompts, few-shot prompting, and chain-of-thought reasoning, to effectively collaborate with business partners in designing agent behaviors.

• Apply knowledge of Retrieval-Augmented Generation (RAG) techniques to ensure agents access proprietary investment data (e.g., PDFs, research reports) accurately, minimizing hallucinations and providing grounded responses.

• Evaluate trade-offs between model performance (e.g., GPT-4o vs. lighter models) and operational factors such as cost and response speed to optimize agent efficiency.

• Leverage familiarity with Microsoft Power Platform, Power Automate, and Custom Connectors to define requirements for seamless data integration from internal databases and third-party providers (e.g., Bloomberg, Morningstar).

• Ensure secure and compliant data access by understanding OAuth, service principals, JSON payload structuring, and implementing safety guardrails to prevent data leakage or unauthorized financial advice.

• Ensure all owned agents comply with enterprise security, data protection, and regulatory requirements.

• Serve as the product representative in architecture, security, and governance reviews.

• Document intended use, limitations, assumptions, and known risks for each agent.

• Act as the primary product point of contact for Copilot Studio developers working on owned capabilities.

• Provide clear acceptance criteria, quality standards, and product guardrails.

• Reduc