Reklaim is building a new way for people to take control of their data — and get paid for it. We operate at the intersection of privacy, data ownership, and consumer rewards.

We have a strong foundation and clear product-market signals. The focus now is scaling — building a repeatable, high-performing growth engine on the consumer side.

The Role

Were looking for a full-stack engineer who works natively with AI development tools to ship production-quality code at startup speed. This is not an "AI-curious" role -- youll be expected to operate Cursor agents, write effective rules and plans, and use AI code review as part of your daily workflow from day one.

Youll work across product and engineering, contributing to architectural decisions, owning features end-to-end, and collaborating directly with product management and marketing. The right person is comfortable context-switching between frontend component work, backend edge functions, analytics instrumentation, and DevOps infrastructure -- and knows when to lean on AI assistance vs. when to think critically.

What Youll Work On

• A React SPA (Vite, TypeScript, Tailwind CSS, shadcn/ui) actively migrating to Next.js (NextForge boilerplate, Payload CMS, Clerk auth)


• Analytics instrumentation across PostHog, GA4 (via GTM), and Braze


• CI/CD pipelines (GitHub Actions), E2E testing (Playwright), and unit testing (Vitest)


• Infrastructure across Vercel, Doppler (secrets management), and AWS (legacy EKS/RDS)

Tech Proficiency Expected

Frontend: React, TypeScript, Tailwind CSS, shadcn/ui, Zod, React Router. Experience migrating between build systems (Vite to Next.js) is a strong plus.

Backend: Supabase (Postgres, RLS policies, Edge Functions), REST APIs, SQL. Familiarity with Deno runtime and npm-specifier-based imports.

Analytics & Data: PostHog (event instrumentation, feature flags, A/B testing), Google Analytics 4, Google Tag Manager (consent mode, tag configuration), and the ability to reason about event schemas and funnel metrics.

DevOps: GitHub Actions, Vercel deployments, Doppler secrets management, DNS configuration. Comfortable setting up CI pipelines, managing setting separation (dev/staging/production), and debugging deployment issues.

AI-Native Development: Daily use of Cursor IDE (agents, background agents, rules, plans). Ability to write effective .cursor/rules/ for project context, review and iterate on AI-generated code, and use GitHub Copilot code review as a quality gate.

Process Proficiency

• Trunk-based development with frequent production releases (2-4/week)






• Linear for issue tracking with T-shirt sizing estimation and cycle-time measurement


• Two-round Copilot review protocol before merge (address comments, push, wait for second pass)


• Playwright E2E tests required for every PR that changes user-facing behavior


• Feature specs maintained in-repo (docs/context/FEATURE_SPECS/) and updated with every behavior change

Stack Summary

• Session context files for multi-session work continuity across AI agents


• PostHog-first analytics: event schema defined in YAML with CI linting; dashboards and funnels used to validate product decisions

What Sets You Apart

• Youve shipped production code using AI agents (Cursor, Copilot, Claude, Codex) and can articulate where they accelerate vs. where they introduce risk


• You instinctively write context (rules, specs, plans) that makes the next agent session productive


• You can own a feature from Linear ticket to production release, including writing the E2E test and updating the feature spec


• Youre comfortable working at the intersection of product and engineering -- translating business requirements into technical decisions without waiting for a detailed spec


• Youve worked in a small team (3-5 engineers) where everyone wears multiple hats


• 100% employer-paid health and dental coverage