Product Engineer

Affinity Labs:
Founding Product Engineer

Location: London Area, United Kingdom
· On-site

At Affinity Labs, we’re building a full-stack AI venture studio that partners with content creators to co-found authentic, scalable software businesses. By combining AI-native development with creator-led distribution, we're pioneering a new model of monetisation by rapidly building, launching, and scaling digital ventures alongside with creators and their audiences.

We aim to launch ventures 10x faster and cheaper than traditional methods using our internal "AI factory": a multi-agent architecture, reusable component libraries, and a growing knowledge graph that learns from every product we ship.

Ship at rapid pace with AI-accelerated workflows, see your work distributed to tens of thousands of users at launch, and compound impact across multiple products, not just one.

You’ll lead end-to-end product engineering across our portfolio: scoping features, designing APIs and data models, building backend services, and shipping polished user-facing experiences across web and mobile.

This is an early-stage, hands‑on role with significant autonomy and responsibility
. You will own full-stack product delivery, from infrastructure and AI integrations through to React / React Native interfaces, collaborating closely with founders, creators, product, and design to turn lean specs into scalable, user-loved software.

We’re looking for a strong generalist with backend depth and real mobile experience.

• Implement features end-to-end (mobile + web frontend → APIs → data models → integrations) while maintaining quality and velocity.
• Build React Native mobile apps and shared component systems across products.
• Design and ship scalable backend services (APIs, integrations, AI workflows).
• Run tight build → test → iterate → ship loops; provide realistic estimates and surface blockers early.
• Manage tech debt pragmatically
• Participate in daily standups and weekly planning;
  contribute to technical strategy and execute from Linear tickets.
• Contribute meaningfully to product and architecture discussions; be heard in debate and align to unified decisions.
• Own operability: CI/CD, monitoring/alerting, performance optimisation, safe rollbacks.
• Build and integrate AI features (LLM/agent workflows, RAG/vector DB integration, eval hooks, cost/safety guardrails).
• Help evolve our reusable product templates and shared architecture across the portfolio.

• 3-6+ years building production-grade full-stack applications, with clear ownership.
• Strong backend experience in Python (FastAPI preferred) and solid database skills (Postgre
  
  SQL/Mongo
  
  DB).
• Proven experience building and shipping mobile apps with React Native.
• Strong React fundamentals (Next.js experience a plus).
• Solid API design and systems thinking.
• Familiarity with AWS serverless patterns and Docker; basic CI/CD concepts.
• Comfortable with Redis (caching/sessions) and queue/messaging patterns.
• Startup mindset
  : high ownership, comfort with ambiguity, bias toward shipping.
• Growth mindset & flexibility: open to feedback; not rigid about stack/tools.
• Clear communicator & collaborator
  ; able to guide product decisions from engineering perspective.
• Evidence of shipping quickly in small teams (links to apps, repos, case studies, live products).

• Node.js alongside Python for services or integrations.
• App Store / Google Play release experience.
• Experience with vector databases (e.g., Chroma) and embedding pipelines.
• Lang Chain or CrewAI for orchestration;
  MCP servers for integrations.
• Security hygiene (secrets, permissions, least-privilege) and practical data-privacy basics.
• Planning & execution in Linear (or similar).

• Backend/Runtime: Python (FastAPI), Node.js.
• Frontend
  :
  React/Next.js
• Mobile: React Native
• Data stores: Postgre
  
  SQL, Mongo
  
  DB (as appropriate), Redis (caching/sessions).
• Vectors/Embeddings: Chroma (or similar).
• AI Models & APIs: Claude (Anthropic), Gemini (Google);
  Amazon Nova Canvas (vision), Deepgram (audio).
• AI Dev Tools: Lang Chain or CrewAI (orchestration), MCP servers (integration), Git Hub Copilot / Claude Code.
• Infra…