Role library
Each role here is defined as a set of skills at required proficiency levels — no years-of-experience field, no degree field, no previous-employer filter. Seniority is expressed as the level, which is both more accurate and more defensible.
Ships end-to-end AI features: designs the system, writes the prompts, builds the evals, and owns whether it works in production.
Owns the production AI system: architecture, reliability, cost, latency, and what happens when the model is wrong.
Owns what the AI product does, what 'good enough' means, and the trade-off between capability, cost, and risk.
Owns the problem being solved, the sequence of work, and the trade-offs nobody else wants to make.
Builds the first version, decides the architecture, and figures out the requirements while shipping.
Finds the constraint, sizes the opportunity, designs the test, and reads the result honestly.
Questions people ask
- Why are there no years-of-experience requirements?
- Because years correlate weakly with capability and strongly with age, career continuity, and luck. Every role here expresses seniority as a required proficiency level on a specific skill, which is both more accurate and more defensible.
- How many skills should a role spec have?
- Four to six. Specs with a dozen required skills are wish lists — they reintroduce the over-filtering that skills-based hiring is meant to remove, and they make your shortlist empty.
- Can I customise a role archetype?
- Yes. Archetypes are starting points — the spec builder lets you add or remove skills, change required levels, and set weights. Nothing here is fixed.