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You will:
- Work closely with AI, product, and design to architect and build features end-to-end (frontend + backend)
- Design and build core application systems: AI agent experiences, data visualization, and a real-time simulation interface for video, audio, chat, and beyond
- Build and maintain backend services and APIs that power simulations, including auth, session management, billing hooks, permissions, and orchestration of AI workflows
- Integrate LLM pipelines and agentic systems into production via robust backend patterns: queues/jobs, rate limiting, retries, caching, and observability
- Own data flows across the stack: schema design, database performance, event tracking, and analytics pipelines that inform product iteration
- Rapidly prototype new AI-driven features—from initial prompt/design to full-stack implementation—and ship in tight loops
- Improve performance and reliability: optimize latency for real-time experiences, harden APIs, and contribute to deployment/infra practices as we scale
- 2+ years of experience as a full-stack engineer, ideally in a startup or similarly fast-paced environment
- Strong with modern frontend technologies (React/Next.js) and solid backend experience building APIs/services (Node.js/TypeScript, Postgres/Supabase or similar)
- Experience with real-time systems (WebSockets/WebRTC) and integrating AI/LLM SDKs (e.g., Vercel AI SDK, LangChain)
- Comfortable with backend fundamentals: API design, database modeling, caching, background jobs/queues, security basics, and monitoring
- Strong product mindset and attention to UX—able to sweat the details and ship polished experiences
- Interest in generative AI, LLMs, RAG pipelines, and agentic architectures
Benefits
Compensation:
Compensation varies based on profile and experience, but a general cash range (fixed comp + performance variable) is $100,000-$250,000, plus a very competitive equity package.
Key Skills
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