Technical Product Owner, Enterprise Search & AI
$145.68k - $178.05k3M Co
Job Description: Technical Product Owner, Enterprise Search & AI Collaborate with Innovative 3Mers Around the World Choosing where to start and grow your career has a major impact on your professional and personal life, so it’s equally important you know that the company that you choose to work at, and its leaders, will support and guide you. With a wide variety of people, global locations, technologies and products, 3M is a place where you can collaborate with other curious, creative 3Mers. This position provides an opportunity to transition from other private, public, government or military experience to a 3M career . The Impact You’ll Make in this Role As a Technical Product Owner for Enterprise Search & AI, you will serve as the critical operational bridge between strategic platform roadmaps and technical sprint execution for 3M’s enterprise search ecosystem. Operating as an individual contributor within a cross-functional pod, you will deconstruct high-level business needs into actionable technical requirements across search infrastructure, AI-powered retrieval, and digital experience platforms, prioritizing the day-to-day tactical backlog to deliver scalable, high-performance search capabilities that power digital commerce, content discovery, and emerging AI applications. Here, you will make an impact by:
- Backlog & Requirement Engineering — Translating the Director of Product & Portfolio Management’s long-term search and AI platform vision into highly detailed user stories, technical specifications, and structured acceptance criteria spanning search API enhancements, ingestion pipeline improvements, index architecture changes, and AI retrieval features.
- Tactical Backlog Prioritization — Owning, refining, and prioritizing the day-to-day pod-level backlog to optimize sprint velocity and engineering throughput across the enterprise search stack, balancing platform reliability work against new AI-driven capabilities such as hybrid retrieval, semantic search, and RAG-enabled experiences.
- Sprint Execution Guidance — Partnering daily with the Enterprise Search Tech Lead and vendor engineers to provide absolute clarity on execution requirements during agile ceremonies, ensuring alignment on search relevance tuning, infrastructure-as-code changes, and AI model integration work.
- Product Quality & Acceptance — Serving as the gatekeeper for user acceptance testing (UAT), verifying that vendor-built and internally developed artifacts strictly adhere to defined technical benchmarks for search performance, relevance accuracy, API response times, and AI output quality before release.
- Adoption & Platform Feedback — Monitoring search platform utilization, tracking adoption metrics across consuming applications (product navigator, digital commerce, AI assistants), and funneling real-world feedback on search relevance and AI feature effectiveness back to the Product & Portfolio Management director.
- AI & Search Capability Evolution — Defining and prioritizing product requirements for the platform’s evolution toward hybrid retrieval approaches combining lexical and semantic/vector search, supporting RAG pipelines, LLM grounding, and agentic AI use cases that drive competitive advantage.
- Multi-Feature Capability Mapping — Mastering competing business group requirements across interconnected search, content, and AI platform modules, governing dependencies and release schedules across ingestion workflows, search APIs, and downstream digital experiences.
- Shared Accountability: Release & Deployment — Co-owning product release schedules and deployment calendar targets alongside Program/Project Managers (PVMO), coordinating CI/CD pipeline releases and infrastructure changes.
- Shared Accountability: Technical Quality — Co-owning software quality metrics, architectural alignment, and technical debt constraints with the Enterprise Search Tech Lead (TSL), including search index health, pipeline reliability, and AI model performance.
- Shared Accountability: Business Value — Co-owning business value metrics and customer satisfaction feedback loops with the assigned Business Relationship Manager (BRM), including search relevance KPIs and AI feature adoption rates.
- Backlog & Requirement Engineering — Translate the Director of Product & Portfolio Management's long-term search and AI platform vision into detailed user stories, technical specifications, and structured acceptance criteria covering search API enhancements, ingestion pipeline improvements, index architecture changes, and AI retrieval features.
- Tactical Backlog Prioritization — Own, refine, and prioritize the day-to-day pod-level backlog to optimize sprint velocity and engineering throughput, balancing platform reliability work against new AI-driven capabilities (hybrid retrieval, semantic search, RAG-enabled experiences).
- Sprint Execution Guidance — Partner daily with the Enterprise Search Tech Lead and vendor engineers to provide clarity on execution requirements during agile ceremonies, ensuring alignment on search relevance tuning, infrastructure-as-code changes, and AI model integration work.
- Product Quality & Acceptance — Serve as the gatekeeper for user acceptance testing (UAT), verifying that vendor-built and internally developed artifacts meet defined technical benchmarks for search performance, relevance accuracy, API response times, and AI output quality before release.
- Adoption & Platform Feedback — Monitor search platform utilization, track adoption metrics across consuming applications (product navigator, digital commerce, AI assistants), and funnel real-world feedback on search relevance and AI feature effectiveness back to the Product & Portfolio Management director.
- AI & Search Capability Evolution — Define and prioritize product requirements for the platform's evolution toward hybrid retrieval approaches (lexical + semantic/vector search), supporting RAG pipelines, LLM grounding, and agentic AI use cases.
- Multi-Feature Capability Mapping — Master competing business group requirements across interconnected search, content, and AI platform modules, governing dependencies and release schedules across ingestion workflows, search APIs, and downstream digital experiences.
- Shared Accountability: Release & Deployment — Co-own product release schedules and deployment calendar targets alongside Program/Project Managers (PVMO), coordinating CI/CD pipeline releases and infrastructure changes.
- Shared Accountability: Technical Quality — Co-own software quality metrics, architectural alignment, and technical debt constraints with the Enterprise Search Tech Lead, including search index health, pipeline reliability, and AI model performance.
- Shared Accountability: Business Value — Co-own business value metrics and customer satisfaction feedback loops with the assigned Business Relationship Manager (BRM), including search relevance KPIs and AI feature adoption rates.
- Bachelor’s degree or higher in Computer Science, Software Engineering, Information Systems, or other technical field (completed and verified prior to start)
- Seven (7) years of experience in technical product ownership, product management, or software engineering, including a minimum of three (3) years owning or managing search, data platform, or AI-driven product portfolios, in a private, public, government, or military environment
- 3M Center, Maplewood, MN or 3M Facility, Austin, TX
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