Sr. Technical Product Manager- Workforce AI

World Wide Technology Healthcare Solutions•Jenks, OK

4h•Hybrid

About The Position

The Sr. Technical Product Manager within the Workforce AI practice leads the discovery, solutioning, and delivery of enterprise AI engagements centered on the Glean AI Platform, with secondary expertise in Google Gemini & Claude. This role sits at the intersection of client advisory, technical presales, and hands-on delivery – serving as the primary client-facing resource who can run a scoping session independently, architect a solution, and lead an engagement from kickoff through value realization. The ideal candidate is fluent enough in platform implementation, agent design, and custom data connector development to hold detailed technical conversations with architects and engineers, while also being comfortable presenting ROI narratives and adoption strategies to C-suite stakeholders. This is not a pure PM role – it requires direct delivery ownership and the commercial instinct to identify and qualify new opportunities.

Requirements

Bachelor’s degree required (Computer Science, Engineering, Robotics, Systems, or related preferred).
6–10+ years of experience in technical product management, solution architecture, or consulting delivery for enterprise software or AI platform engagements.
Demonstrated success supporting presales independently: running discovery sessions, building solution narratives, creating estimates, and contributing to proposals and executive presentations.
Working knowledge of agent design principles: prompt engineering, tool/function definition, multi-step orchestration, and agent testing and governance.
Experience scoping or overseeing API-based integrations and custom data connectors, including understanding of REST/GraphQL, authentication patterns (OAuth, SAML), and permissions/IAM models.
Strong understanding of enterprise AI concepts – RAG, semantic search, embeddings, LLM grounding – and the ability to translate them into client-facing business value narratives.
Proven ability to manage cross-functional delivery teams and hold accountability for engagement outcomes in a consulting or professional services environment.
Excellent communication and stakeholder management skills: equally comfortable in a technical architecture review and a C-suite ROI conversation.

Nice To Haves

Direct Glean platform experience: Glean admin, Agent Builder, connector framework, or Glean API.
Experience with Google Gemini and Claude Enterprise.
Familiarity with data platforms (Snowflake, Databricks, BigQuery) in the context of enterprise AI grounding and semantic layer design.
Experience designing or facilitating organizational change management programs, Center of Excellence models, or AI adoption strategies.
Understanding of enterprise security architecture as it relates to AI platforms: IAM, SSO, data classification, and permissions enforcement.
Familiarity with MCP (Model Context Protocol) and emerging agentic integration standards.
Experience using AI-assisted development tools to accelerate prototyping and delivery (e.g., Claude Code, Cursor, Cognition, or similar).
Hands-on familiarity with Glean or a comparable enterprise AI search/knowledge platform (e.g., Microsoft Copilot, Coveo, Guru, Notion AI), with the ability to ramp quickly on Glean-specific capabilities.
Master’s degree a plus (AI/ML, Robotics, Computer Vision, Systems Engineering, HCI).

Responsibilities

Lead discovery workshops and scoping sessions independently, translating client business challenges into a structured engagement model across the Workforce AI service pillars.
Build and present solution narratives, demos, POCs, and estimates; contribute to proposals and executive-ready presentations that articulate platform value and projected ROI.
Guide clients through platform selection, use case prioritization, and build-vs-buy decisions across AI solutions, drawing on a clear understanding of each platform’s strengths, limitations, and integration patterns.
Develop trusted advisor relationships with client stakeholders from Business and IT through to CISO, CIO, and CTO.
Provide Product Management leadership on engagements – from platform deployment and user enablement through agent design, custom connector build, and multi-agent ecosystem extension.
Partner with AI architects, integration engineers, data platform engineers, and change management leads to ensure technical quality and on-time delivery.
Maintain hands-on involvement in platform configuration, agent design reviews, connector scoping, and security/permissions validation – enough depth to unblock teams and make real-time scoping decisions.
Develop and iterate ROI frameworks tied to measurable business outcomes (e.g., time saved, adoption rates, support deflection, onboarding acceleration).
Leverage AI tools and continue to evolve the delivery practice for efficiency and better outcomes.
Working knowledge of AI Platforms: enterprise search, agent building, connectors (native and custom).
Ability to scope and implement agent workflows, including tool definitions, prompt design, multi-step orchestration, and agent lifecycle governance.
Experience scoping and overseeing connector development.
Ability to compare AI Platform (e.g. Glean, Gemini, Claude, Copilot) capabilities in context of a client’s existing investment and recommend a prioritized, integrated approach.
Lead or oversee executive alignment sessions, persona-based change planning, communications strategy, and user training programs tied to AI Platform adoption across departments.
Design or guide Center of Excellence (CoE) and Champions program structures that sustain adoption beyond initial deployment.
Define success criteria, adoption KPIs, and business outcome frameworks for each engagement phase.
Embed responsible AI practices throughout engagement delivery: data privacy, permissions enforcement, IAM review, transparency, and audit readiness.
Ensure Glean deployments respect source system access controls end-to-end, and that agent and connector designs pass security review.
Guide clients on AI governance frameworks for agent lifecycle management, including testing, versioning, and change control.