Kinect — Backend Engineer

Type: Full-time | On-site | San Francisco, CA Compensation: $120,000–$150,000 + Competitive equity Hiring count: 1 Visa sponsorship: None available Reports to: Co-founder (two-person engineering team)

Kinect is building an AI revenue platform for D2C brands with a heavy e-commerce focus, integrating with major platforms including Shopify, Salesforce Commerce Cloud, and Adobe Commerce. It helps mid-market and enterprise D2C brands build AI automations and tooling that drive more sales on- and off-platform, and runs its own internal analytics platform to track feature usage and performance.

Three months old, YC-backed, already at $250K ARR and working with brands representing over $50M in GMV. Runway is comfortable for at least 18 months, and the founders project 8x growth to $2–5M ARR by year-end. Founded and run by two technical co-founders who still code daily.

Founded: 2026 (3 months old at posting) | Team size: 1–10 (two-person engineering team) | Total funding: Not disclosed (YC-backed) Industry: eCommerce, D2C, AI Website: https://trykinect.ai Office: San Francisco, CA

• Ground-floor ownership: Platform infrastructure, feature engineering, workflows, and observability tooling don't exist yet — you build them from scratch.
• Real traction, early: YC-backed, $250K ARR at three months, brands worth $50M+ in GMV, 18+ months runway, and a projected 8x to $2–5M ARR by year-end.
• AI-native by default: The founders barely read code by hand; heavy AI-tool development is the expected way of working, not a novelty.
• Direct to the founders: Two technical co-founders who still code daily — you report straight to one on a two-person engineering team.

• AI-native coding fluency is explicitly the #1 priority — the founders barely read code manually and expect heavy AI-tool development from day one.
• Past MVP with live customers; now building platform-level infrastructure, feature engineering, workflows, and observability from scratch (none currently exists).
• Stack (TypeScript on Fly.io) was chosen recently as the founders build past their comfort zone — adaptability matters more than deep stack-specific experience.
• Two-person engineering team; role reports to a co-founder.
• Some forward-deployed, customer-facing work is a plus — translating direct customer feedback (sometimes just a meeting summary) into shipped features.
• Creative comp structures considered, including revenue-target bonuses.

Backend Engineer with a data-engineering lean, building the data enrichment, normalization, and ingestion pipelines that power the platform, plus the platform infrastructure and tooling that doesn't yet exist.

• →Build and maintain data enrichment, normalization, and ingestion pipelines
• →Build feature engineering and platform infrastructure, including observability and workflow tooling that doesn't yet exist
• →Work extensively with AI coding tools as a core part of daily development, not an occasional aid
• →Translate customer feedback and requirements directly into shipped features, sometimes working from a meeting summary rather than a formal spec
• →Contribute independently to systems and data-layer design decisions

Tech stack: TypeScript on Fly.io (recently adopted; adaptability valued over deep stack-specific experience)

• Strong proficiency in using AI coding tools as a primary part of the development workflow (top priority)
• Solid systems engineering fundamentals: understands how features work end-to-end and how to build data layers
• Demonstrated startup experience with genuine ownership of what was built
• Comfortable with high-intensity pace: 5-6 days a week
• Experience: 0–2 years

• Fluent, heavy use of AI coding tools as a core part of daily development
• Genuine startup ownership: built and was responsible for real systems, not just features on a larger team
• Comfortable working from ambiguous input, such as a customer meeting summary, and independently shaping the solution
• E-commerce, D2C, or platform integration domain exposure
• Track record suggesting the ability to eventually hire and lead a small team

• Career built entirely at large enterprise or post-Series D companies with heavily defined processes
• Relies on manual coding without meaningful AI tool fluency
• Cannot demonstrate genuine ownership of what was built in past roles
• Short tenure pattern without a legitimate explanation (contract-based roles ending due to funding changes are understood and not held against a candidate)

• Location: San Francisco, CA
• Work policy: On-site — 5-6 days a week
• Compensation: $120,000–$150,000 + equity
• Visa sponsorship: None available
• Employment type: Full-time

None provided in the role posting.

Stage 1 — Behavioral vibe check call — Initial behavioral / culture-fit conversation. Stage 2 — Take-home assignment — Take-home build. Stage 3 — Live interview — Candidate presents the take-home and extends it with an additional feature. Stage 4 — Work Trial — One-to-two-day paid work trial. Stage 5 — Offer Extended Stage 6 — Candidate Hired — Candidate accepts and starts.