WHAT YOU'LL GET TO DO

Architect AI Tools

• Lead the end-to-end design and development of AI-powered internal applications that improve operational efficiency across departments.
• Translate complex, ambiguous business needs into scalable, maintainable systems used daily by internal teams.
• Build modular architectures that connect data ingestion, AI processing pipelines, and front-end interfaces

LLM & AI Integration

• Architect and implement LLM-powered features using advanced patterns including: RAG pipelines, multi-agent orchestration, function calling, embeddings, and more
• Evaluate emerging AI frameworks and make sound decisions about when and how to adopt them
• Ensure AI systems are reliable, observable, and built with responsible practices in mind.

Full-Stack Engineering

• Design and maintain production-grade REST/GraphQL APIs and front-end experiences using JavaScript/TypeScript and modern frameworks
• Own database architecture and performance: PostgreSQL/Supabase, SQL tuning, caching strategies, and vector stores (Pinecone, pgvector, or similar)
• Manage deployments, observability, and scaling across cloud/serverless infrastructure (Vercel, AWS Lambda, or similar)

Technical Leadership

• Set engineering standards and mentor teammates on best practices, architecture decisions, and AI integration patterns
• Lead code reviews and contribute to a culture of quality, speed, and continuous improvement
• Partner with product leadership to prototype, validate, and scale AI- driven tools.