- Applied-AI product engineer (NOT ML/data-research)
- Shipped AI-in-product; tuned LLM-tooling workflow
- ~8–10 yrs; startup/ex-founder strong signal
- "Happy warrior" culture fit
Mento is hiring a product-minded senior software engineer with data experience to help build its differentiated AI + software coaching product and the AI/software tools that augment human coaches. Critically, this is the applied-AI / full-stack-product archetype — someone who's figured out how to incorporate AI into real products — not the data-engineering/ML-research profile (Kevin sees both apply to "AI Engineer" and wants the former). You'll join a small, fast, flat team and work closely with design and coaching to ship a compelling product experience.
The work is 0→1 and product-focused (you'll ship regularly, make technical trade-offs, take risks): designing AI-enabled capabilities on top of foundation models (structuring them for adaptability, reuse, scalability), translating coaching insights/workflows into high-quality AI-agent product experiences alongside Mento's coach network, building data pipelines and integrations across a wide productivity/L&D ecosystem, and mentoring the team on AI/data best practices. Kevin's biggest differentiator among strong candidates: critical thinking about technical choices — can they walk through a project they built, explain their choices with a crisp mental model, and reason clearly when pushed on "what would you change" or "how would you add this feature."
Key Responsibilities
- Build features and experiences 0→1; ship regularly, make trade-offs, take risks
- Design AI-enabled capabilities on top of foundation models — structured for adaptability, reuse, scalability
- Work with coaching to translate coaching insights/workflows into high-quality AI agents
- Build pipelines and integrations to import/export data across the productivity/L&D ecosystem (scalable, reusable)
- Educate the team on data/AI best practices — peer mentorship, code reviews, lunch-and-learns
Requirements
- Product-minded senior engineer who's shipped data-related products into production with real users (not a new grad)
- Applied-AI / full-stack product profile — has incorporated AI into products; not an ML/data-engineering-research profile
- Sophisticated, far-down-the-curve user of LLM coding tools (Cursor, Cody, etc.) — has a genuinely tuned process: knows when they work, how to validate outputs, how to automate more of their flow. (There's a live coding interview on this; surface-level adopters fall out.)
- Server-side web app experience; comfortable in dynamic languages; ideally event-driven architectures + traditional web stacks (Rails/Laravel). Stack is Go/TypeScript/Ruby — specific stack matters less than adaptability (web/full-stack/back-end fine; pure mobile or embedded-only is a harder adaptation)
- Core data-engineering / software-architecture opinions (search indexes, data pipelines)
- Critical thinker with a crisp mental model of what they build and why (the top differentiator)
Execution and Ownership
- Startup experience — big-tech + consulting only is a failure mode (unless clearly high-ownership within it). Comfortable with ambiguity, directness, fast decisions
- Treats "make the team better" as an opportunity, not a threat — shares best practices, flags broken processes, peer-mentors
- Comfortable with high ownership, flat structure, and direct access to (and disagreeing with) a founder-CEO
- Excited by LLM coding tools rather than threatened
Background
- ~8–10 years (L3 target); truly exceptional senior (20-yr) possible but not the current aim; genuinely exceptional long-time coders with only a couple industry years not an automatic no; not new grads / not "still getting their feet wet"
- Former founders are a strong signal (most of the team, incl. Kevin, the lead candidate, and the new PM, are ex-founders)
- Senior leaders who want to be an IC right now (not manage) fit well
- Mission-driven ("missionaries over mercenaries") — bought into human-centered coaching; the wrong candidate asks "why aren't you automating the coaches away?"
Culture Fit ("Happy Warriors")
- Ambitious and hard-charging but fun — goofy, not teeth-gritting; "happy warriors"
- Quirky / has a genuine outside-of-work "thing" — pure 9-to-5 normies aren't the crew
- High-challenge coaching culture (high performance, direct feedback), not just "nice"
Who Will Thrive Here
- A product-minded full-stack engineer who's shipped AI-in-product and has a genuinely tuned LLM-tooling workflow
- An ex-founder / high-ownership operator who wants a flat, direct, founder-adjacent seat
- A critical thinker who can defend every technical choice with a crisp mental model
- A mission-driven "happy warrior" excited to augment (not replace) human coaches
- Someone who wants IC impact and to make the whole team bette