Technical Product Manager

Specific Responsibilities

Learner Supply & Instrumentation

• Build a repeatable pipeline of beta learners, engaging the right internal teams to keep them flowing — the constraint that gates everything else, and it rewards hustle over process.
  
• Instrument the AI products in partnership with the LLMOps Engineer — you instrument; they build the evals over what is captured.
  

The Experiment Loop

• Own the experiment loop — a backlog of the team’s biggest uncertainties, experiments designed against them, cycle time measured and shrinking.
  
• Close the loop: data reviewed, UX and learning validation captured, improvements shipped, and the next PoC out the door.
  

Skill Requirements - Essential

• Product experimentation: you have run it end-to-end, hypothesis, instrumentation, decision. A/B testing or structured product testing on a live product.
  
• Technical fluency: you can talk concretely about instrumenting a product, read AI-eval results, and hold your own with engineers. You don’t need to code daily.
  
• Operator ability: recruiting and coordinating real users, running a beta programme, and wrangling stakeholders.
  
• Desirable (not required): hands-on eval or analytics skills; EdTech experience.
  

Essential Traits for Success

• You have a scientific mindset. You know what an experiment can and can’t conclude, and your favourite experiments include ones that killed an idea you loved.
  
• You’d enjoy the question “how would you get 50 beta learners in two weeks with no budget?” enough to start answering it in the interview.