Principal Technical Product Manager - AI Frontiers
New
U
UpworkAI & Technology
We currently hire full-time employees in 34 U.S. statesFull-TimePrincipal
Salary$190,500 — $384,750 USD
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Job Details
- Required Skills
- Artificial IntelligenceMachine LearningProduct ManagementRESTful APIsData modelingLLM
Requirements
- Track record of 0-to-1 product leadership, taking ambiguous, early-stage products from concept to real users and revenue.
- AI-native product judgment grounded in agentic and LLM-driven systems, including human-in-the-loop design.
- Hands-on technical ability to prototype ideas and vibe-code working demos using AI coding tools.
- Fluency in technology to build and pressure-test concepts alongside engineering teams.
- Ability to partner with engineering leaders on API boundaries, data modeling, and build-vs-buy trade-offs.
- Service design and operations sensibility that treats human-ops programs as part of the product.
- Executive-grade communication skills with a bias to ship and a direct approach to feedback.
- Capacity to operate when specs are half-written and navigate early-stage ambiguity.
Responsibilities
- Own the product end-to-end, setting the vision and roadmap, writing and maintaining the spec, and making hard scope calls across a multi-stage, AI-assisted workflow.
- Drive the human-to-AI progression by deciding which human steps to automate first and instrumenting the system for seamless AI integration.
- Coordinate a broad cross-functional surface across engineering, design, data, and platform partners to keep a high-velocity core team unblocked.
- Run the operational program in partnership with Operations, scaling the human expert function and playbooks while reducing human effort per engagement.
- Own go-to-market for early cohorts alongside sales and customer engagement, sharpening the value proposition and protecting the business model.
- Present progress, learnings, and decisions to leadership, translating early-stage reality into strategic recommendations.
- Run the learning agenda by turning workflow steps into structured data and using quantitative and qualitative signals to drive development.
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