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Kinect — Backend Engineer

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: davidjoseph-co
Full Time position
Listed on 2026-07-21
Job specializations:
  • Software Development
    Backend Developer, Cloud Engineer - Software, Full Stack Developer, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 150000 USD Yearly USD 120000.00 150000.00 YEAR
Job Description & How to Apply Below

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)

About Kinect

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, AIWebsite: (Use the "Apply for this Job" box below). Office:
San Francisco, CA

Why Candidates Should Join
  • 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.
Intake Call Summary
  • 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 (Type Script 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.
The Role

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.

What You'll Be Doing
  • 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: Type Script on Fly.io (recently adopted; adaptability valued over deep stack-specific experience)

Requirements
  • 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
Green Flags
  • 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
Red Flags
  • Career built entirely at…
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