Technical Product Lead

High Bridge Consulting LLC

. Define KPIs for commercial knowledge accuracy, freshness, ownership, review adherence, reliability and AI readiness .

Posted 11/3/2026full-timeRemote • United StatesSenior💰 $50 - $70 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing enterprise AI solutions, focusing on knowledge architecture, content governance, and integration of AI capabilities. Proven ability to lead cross-functional teams and translate complex technical requirements into scalable, actionable strategies.

Highest-signal resume keywords

Enterprise AI DevelopmentKnowledge ArchitectureContent GovernanceAPI IntegrationCross-Functional Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Generative AIRetrieval-Augmented GenerationKnowledge TaxonomyContent Lifecycle ManagementContent Quality MeasurementAI Reliability AssessmentPythonSQLLow-Code DevelopmentMulti-Agent Orchestration

Soft Skills

Technical LeadershipCross-Functional CollaborationProblem SolvingCommunication

Tools & Technologies

Microsoft 365SharePointCopilot StudioPower PlatformPower AutomateMicrosoft GraphAzure AIAPIsJSONCloud Architecture

Industry Keywords

AI CapabilitiesEnterprise KnowledgeSemantic SearchInformation GovernanceContent Review Standards

Tech Stack

Tools & technologies

AzureCloudPythonSQL

About the role

Key responsibilities & impact

Define KPIs for commercial knowledge accuracy, freshness, ownership, review adherence, reliability and AI readiness
Establish baselines for trusted knowledge and identify areas requiring intervention
Measure and advance content review and governance automation
Create actionable reporting on healthy, stale, unowned or unreliable content
Define the architecture and roadmap for agentic knowledge capabilities
Lead or directly support development and prototyping of AI agents grounded in enterprise knowledge
Design collaboration among multiple agents and AI capabilities
Establish retrieval, grounding, integration, security and evaluation standards for production agentic capabilities
Translate emerging AI capabilities into practical commercial use cases with technical resources
Define onboarding and adherence models for internal knowledge providers
Establish standards for content review, metadata, taxonomy, ownership, lifecycle and governance
Create a scalable enterprise knowledge framework that other internal organizations can adopt
Enable trusted knowledge consumption through search, enterprise workflows and AI/agentic experiences
Lead technical product/program initiatives from concept through prototype, deployment and measurable adoption

Requirements

What you’ll need

Demonstrated experience taking enterprise AI, Generative AI or agentic solutions from concept through production and adoption
Strong working knowledge of LLMs, Retrieval-Augmented Generation (RAG), enterprise/semantic search and agentic architectures
Experience designing or directing agent workflows, retrieval and grounding approaches
Experience integrating enterprise knowledge and data through APIs, connectors, retrieval pipelines or similar integration approaches
Strong understanding of knowledge architecture, taxonomy, metadata, content lifecycle and information governance
Experience measuring content quality, retrieval effectiveness, AI reliability and/or user adoption
Sufficient technical depth to work directly with engineers and architects, challenge technical decisions and translate business requirements into scalable solutions
Demonstrated ability to lead complex cross-functional technology programs and technical resources
Experience 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
Experience 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