Product Manager, Internal AI

Role Description

This is Terawatt's product lead for internal AI. The Product Manager's goal is to make Terawatt AI-native by building the internal operating system. This position will define and execute the strategy for how every Terawatt employee across Development, Finance, Operations, and Technology uses AI to work faster, with better judgment, and at greater scale. You will own the roadmap, ship internal tools, drive adoption, and report impact directly to the C-suite.

This role is focused exclusively on how Terawatt's own teams work — it is distinct from AI applied to our customer-facing CMS or energy products. If you're an operator, builder, or strategist who's been asking yourself "how do I get closer to building something?" — this opportunity is for you.

Core Responsibilities

Lead cross-functional discovery across all Terawatt teams (e.g. Development, Finance, Operations, and Technology) to identify high-leverage pain points and prioritize these by business impact 

Define product requirements, build prototypes using AI tools, gather user feedback, and iterate rapidly — owning the full product lifecycle from zero to deployed

Scale solutions that gain internal traction by leveraging engineering resources to harden, integrate, and expand proven tools

Define and report on adoption and impact metrics (hours saved, workflows automated, % active users) to the executive team

Communicate clearly and compellingly to C-suite stakeholders on the business value delivered

Run the internal AI intake and prioritization process: source use cases from every function, evaluate ROI, and maintain a transparent roadmap

Partner with the Technology, Legal, and Security to own responsible-use guardrails for internal AI — including model evaluation, data handling, and security policy.

Lead change management and enablement — training, prompt libraries, internal community — so AI tools are actually used, not just shipped

Minimum Qualifications

Bachelor’s or Master’s degree in computer science, engineering, information systems, business administration or related field.

5+ years experience in a highly cross-functional, fast-paced environment — management consulting, investment banking, product management, or a top-tier operating role

Demonstrated hands-on AI fluency (e.g., shipped an AI-powered application, or led an AI rollout)

The ability to go from ambiguous problem to a structured approach and solution fast, even with fragmented operational systems and messy real-world workflows

Comfort with unstructured environments where you create the playbook, not follow one

Exceptional written and verbal communication skills; you can speak the language of both engineers and executives (incl. setting metrics/KPIs and reporting on these on a regular cadence)

Experience influencing senior stakeholders without direct authority and getting cross-functional teams to adopt new tools and processes

Comfort working closely with engineers — writing specs, debugging in a notebook, reviewing model outputs — even if you don’t write production code

Preferred Qualifications

Demonstrated leadership experience in setting up new processes and solutions

Prior experience with product management processes, such as developing user stories, completing Jobs-to-be-Done frameworks, and defining system architectures 

Academic background or prior experience in software engineering 

Experience deploying internal AI tools (e.g. Copilot, ChatGPT Enterprise, Glean, custom RAG, agents) at a 100+ person company

Bias toward shipping small, useful loops quickly.

Familiarity with AI evaluation or governance frameworks