Technical Product Lead

This is a fully remote position, open to applicants in United States.

📋 Description

• Set key performance indicators (KPIs) for the accuracy, freshness, ownership, review compliance, reliability, and AI readiness of commercial knowledge.

• Establish benchmarks for reliable knowledge and pinpoint areas that need improvement.

• Assess and enhance the automation of content review and governance.

• Generate actionable reports on content that is healthy, stale, unowned, or unreliable.

• Define the framework and strategy for agentic knowledge capabilities.

• Lead or directly assist in the development and prototyping of AI agents based on enterprise knowledge.

• Design collaborative processes among various agents and AI functionalities.

• Set standards for retrieval, grounding, integration, security, and evaluation for production agentic capabilities.

• Translate emerging AI advancements into applicable commercial use cases utilizing technical resources.

• Define models for onboarding and adherence for internal knowledge providers.

• Establish guidelines for content review, metadata, taxonomy, ownership, lifecycle, and governance.

• Create a scalable enterprise knowledge framework that can be embraced by other internal organizations.

• Facilitate trusted knowledge consumption via search, enterprise workflows, and AI/agentic experiences.

• Guide technical product/program initiatives from the initial concept through to prototype, deployment, and measurable adoption.

⛳️ Requirements

• Proven experience in taking enterprise AI, Generative AI, or agentic solutions from the conceptual stage to production and adoption.

• Strong practical knowledge of LLMs, Retrieval-Augmented Generation (RAG), enterprise/semantic search, and agentic architectures.

• Experience in designing or overseeing agent workflows, retrieval, and grounding methods.

• Background in integrating enterprise knowledge and data through APIs, connectors, retrieval pipelines, or similar integration techniques.

• In-depth understanding of knowledge architecture, taxonomy, metadata, content lifecycle, and information governance.

• Experience in measuring content quality, retrieval efficiency, AI reliability, and/or user adoption.

• Adequate technical expertise to collaborate with engineers and architects, question technical decisions, and convert business requirements into scalable solutions.

• Demonstrated capability to lead complex cross-functional technology programs and manage technical resources.

• Familiarity with AI and retrieval technologies including LLMs, RAG, agentic AI, multi-agent orchestration, semantic search, embeddings, vector search, AI grounding, and evaluation.

• Experience with APIs, JSON, enterprise connectors, structured/unstructured data, authentication/permissions, and cloud architecture.

• Familiarity with Microsoft 365, SharePoint, Copilot Studio, Power Platform, Power Automate, Microsoft Graph, and/or Azure AI.

• Working knowledge of Python, SQL, low-code development, APIs, and modern AI prototyping techniques.

🏝️ Benefits

• Comprehensive health and wellness benefits.

• Opportunities for professional development and career advancement.

• Flexible work arrangements to promote work-life balance.

• Collaborative and inclusive company culture.