Senior Product Engineer (Product-leaning)

**Kickoff** Senior Product Engineer (Product-leaning); $200K–$230K base + equity (0.2%–0.5%); New York City (On-site)

**About Company** Kickoff is the first platform to offer personal training covered by health insurance, on a mission to refocus healthcare on prevention. Clients are matched with a coach who is both a certified personal trainer and a registered dietitian, delivering a comprehensive program across exercise, nutrition, sleep, and disease prevention — with a human in the loop for accountability. Because Kickoff can demonstrate dramatic, measurable health improvements (clients targeting weight loss typically lose ~5% of body weight in the first two months), insurance partners foot the bill, making it $0 out-of-pocket for most members.

The company has scaled from $0 to a ~$17.3M annualized revenue pace in nine months — a pace rarely seen in health tech, with growth still accelerating (June revenue up 32% vs the same point in May) — backed by investors including 645 Ventures, FJ Labs, and Expa. The product integrates with the full range of wearables and health devices (Strava, Samsung Health, and more) to pull in far more signal on each client than a human could process, and uses the latest AI models to recommend the next best step for every client and coach.

**About the Role** This is the product-leaning of two Senior Product Engineer seats: a PM who can flex into AI engineering with AI help. You'll own product areas end-to-end — discovery, hypotheses, specs, design direction — and ship real features yourself using AI coding tools, partnering closely with the engineering-leaning product engineers and the founder/CEO. Same mission and surface as the sibling seat, with much of the work centered on Kickoff's recommendation engine and a current rebuild of the workout-creation experience. The bar on deep full-stack engineering is lighter here than for the engineering-leaning seat — what matters most is product judgment plus the ability to build with AI.

**Responsibilities** - Own product areas end-to-end: discovery, hypotheses, specs, design direction, implementation (AI-assisted), QA, launch, and metrics. - Build delightful consumer- and coach-facing experiences across web and mobile, shipping via AI/agentic tools. - Shape AI-powered features that personalize workouts, nutrition, habits, and sleep, and surface meaningful patterns in client data. - Partner with engineers on the harder technical builds; define specs, evals, and success metrics for AI features. - Work directly with coaches and clients to find high-leverage problems and own the metrics you move.

**Required Skills** A. Strong product judgment and UX instincts — decides what to build, how it should work, and what to leave out; uses AI design tools to make it clean and clear (designer-level finesse not required). B. Operates at the forefront of AI and can flex into engineering with AI help — comfortable reading and modifying code and shipping production features via AI coding tools, even if not a deep full-stack engineer. C. Expert at improving LLM outputs over time with evals and fine-tuning. D. Proven consumer / B2C / prosumer product experience — has demonstrably built beautiful, intuitive consumer-grade interfaces (consumerized B2B such as Mercury counts). E. Can move from user interview to prototype to production quickly and independently (with AI assistance).

**Bonus Skills** - Hands-on full-stack React/Node ability (a plus here; the hard requirement sits with the engineering-leaning seat). - Has built highly customized coding workflows/harnesses with Claude, Codex, and/or Cursor. - Has built AI agents that do valuable work for them or their company. - Built health, wellness, fitness, or other relevant consumer products with excellent UX. - Has been a founder or early-startup employee; active in the NYC tech/startup community.

**Logistical Info** - Location: New York City, in-office 4–5 days/week (4-day minimum). Commute must be ~45 minutes or less — NYC, Jersey City, Hoboken, or close Westchester are fine; Princeton/New Haven-type commutes won't work. - Compensation: $200K–$230K base + 0.2%–0.5% equity. $230K is a hard ceiling; candidates who will only accept $250K+ are out of scope. - Number of openings: 1 — the product-leaning seat (one of two Senior Product Engineer hires; both being hired ASAP). - **Other:** Visa transfer sponsorship and relocation possible for the right candidate (transfers, not new visas).

**Ideal Background** - Strongest signal — insurance-covered consumer services (great talent pools for us): Headway, Grow Therapy, Talkiatry, Alma, Rula, Allara, Midi Health, Maven Clinic, Tia, Parsley Health, One Medical, Included Health, Ro, Hims & Hers, Thirty Madison, Spring Health, Modern Health. - Also strong — innovative, well-designed consumer wellness: Strava, AllTrails, Oura, Whoop, Levels, Eight Sleep, Tonal, Future, Ladder, Runna, Garmin, Headspace. - Also strong — other beautifully-designed consumer / consumerized B2B: Betterment, Mercury. - Lean toward product managers / product engineers with real building instincts — the difference from the sibling seat is emphasis, not mission or bar.

**Green Flags** - Entrepreneurial and high-urgency (KEY for their team) — forms own product hypotheses, pushes the company to move faster and do more, and owns their metrics and goals. - High autonomy and ownership; ships features end-to-end with little process. - Genuinely motivated by Kickoff's preventative-health mission. - AI-native: uses AI/agentic tools across research, design, build, and QA every day.

**Red Flags** - Pure PM with no ability or willingness to build, even with AI help. - Uses AI tooling only superficially — not pushing the edge. - No demonstrable consumer-grade UI/UX product work. - Lukewarm or low-energy; waits for specs rather than forming their own hypotheses. - Comp expectations above the $230K ceiling; commute over ~45 minutes. - Currently at a direct competitor — Nourish, Fay, Berry Street (avoid outreach).

**Interview Process** 1. Round 1 — call with Jack (founder/CEO). 2. Round 2 — with senior product engineer Blake. 3. Round 3 — any additional questions from Jack; often skipped, otherwise in-person with Jack and possibly a few team members briefly. 4. Round 4 — paid 3-hour in-person project (paid hourly), working side-by-side with the product engineering team using AI tools, followed by a discussion. 5. Final round — with the head of operations, head of growth, an engineer, and Jack. Reference checks at the end.