Agent Building Blocks Technical Product Manager

What you'll do

• Develop a product strategy and vision for reusable agent building blocks like memory, runtime, and connectors.
• Own and maintain the product backlog for memory, harness, reusable agents, and top connectors.
• Engineer a governed memory-as-a-service platform featuring episodic and semantic recall with entitlement-aware scoping.
• Establish the Harness as the firm-grade runtime for long-running agents and ship reusable agents as configurable templates.
• Consolidate fragmented agent implementations into a single platform featuring fine-tuned models and UI-based fine-tuning.
• Execute the top-connector backlog for systems like M365, ServiceNow, and Salesforce as distributed, governed assets.
• Partner with data teams to deliver secure, governed access to structured and unstructured data in line with firm policy.
• Track key success metrics including component reuse, memory convergence, connector adoption, and system reliability.

What we're looking for

• 5+ years of experience or equivalent expertise in AI product management or a relevant domain area.
• Advanced knowledge of the Agent development life cycle, Spec Driven Development, design, and data analytics.
• Proven ability to lead product life cycle activities including discovery, ideation, strategic development, requirements definition, and value management.
• Demonstrated experience with AI and agentic products or platforms, including foundational concepts such as LLMs and Harness.
• Hands-on experience using LLMs and AI-powered tools to drive personal and team productivity.
• Familiarity with evaluating and instrumenting AI systems to measure quality and performance for non-deterministic, agent-driven experiences.
• Proven track record of delivery and new product feature creation through agile product development and the software delivery life cycle.
• Strong stakeholder management, strategic thinking, and the ability to influence and align cross-functional partners.
• Experience defining or managing reusable technology assets such as components, templates, connectors, or shared services (preferred).
• Working understanding of retrieval-augmented generation, agent memory, prompt management, and natural language to SQL (preferred).
• Familiarity with data integration and connector patterns across sources like M365, ServiceNow, Salesforce, Snowflake, and Databricks (preferred).
• Understanding of agentic patterns such as orchestration, tool use, multi-step reasoning, and human-in-the-loop design (preferred).
• Exposure to model fine-tuning, evaluation of retrieval and query quality, and vector stores (preferred).
• Awareness of Responsible AI principles, including safety, fairness, and governance (preferred).
• Experience benchmarking reusable components against internal targets and external industry benchmarks (preferred).