Frontend Developer

Syce is looking for a Full Stack AI Engineer to join its engineering team and help build modern AI-powered software products. The role involves working across frontend, backend, and applied AI, taking features from concept through implementation and production in a fast-moving startup environment. Responsibilities: • Develop responsive web applications using React, Next.js, and TypeScript • Build backend services and REST APIs using Node.js • Design and maintain database models and application services • Build and integrate AI and LLM-powered application features • Work with LLM APIs, structured outputs, and tool or function calling • Develop AI agents and automated workflows • Implement RAG, embeddings, and semantic retrieval where appropriate • Integrate third-party APIs and external services • Build secure authentication and authorization flows • Develop asynchronous and background processing • Improve application performance, reliability, and scalability • Implement testing, logging, monitoring, and AI observability • Deploy and maintain applications in cloud environments • Participate in architecture and technical design discussions • Prototype new technologies and turn successful experiments into production-quality features • Work collaboratively through Git-based development, code reviews, and CI/CD The role offers the opportunity to work directly with the founding team, build production software from an early stage, and experiment with emerging AI technologies.

Core Skills: • JavaScript / TypeScript • React • Next.js • Node.js • REST APIs • MongoDB or similar databases • HTML/CSS and responsive UI development • Git and GitHub • Cloud deployment AI Engineering: • Experience integrating LLMs into applications • Prompt engineering • Structured LLM outputs • Function or tool calling • AI agents and workflow orchestration • RAG • Embeddings and vector search • Context management • AI evaluation, monitoring, and debugging Good to Have: • Python • AWS or Azure • Docker • Redis • PostgreSQL • Vector databases • MCP (Model Context Protocol) • LangGraph or similar frameworks • WebSockets / real-time applications • Data pipelines • Recommendation systems • Multi-agent systems • AI security and guardrails • SaaS application development What We're Looking For: • Ability to independently take a feature from requirement to production • Understanding of both software engineering and practical AI implementation • Ability to work across frontend and backend • Ability to experiment quickly while writing maintainable production code • Understanding of reliable AI application development beyond simply calling an LLM API • Comfort working in an early-stage environment where requirements evolve quickly • Clear communication of technical decisions • Strong ownership of problems and outcomes