About the Role
You\'ll own features end to end — from data model and API to UI and deployment — across our web applications and AI products. This is a hands-on senior role: you\'ll architect and build full-stack systems, integrate LLM-driven capabilities (agents, retrieval, tool/function calling), and take responsibility for quality, performance, and shipping. You\'ll work in both TypeScript/Node and Python ecosystems depending on the engagement, deploy to AWS or Azure, and collaborate closely with data scientists, designers, and client stakeholders.
Responsibilities
- Design, build, and ship full-stack features across frontend, backend, and data layers.
- Build and consume well-designed REST/GraphQL APIs and services; model the data behind them.
- Develop modern, responsive UIs and the server-side logic that powers them.
- Integrate LLM/AI capabilities into applications — agents, retrieval-augmented generation, tool/function calling, and orchestration.
- Deploy, monitor, and maintain applications on cloud infrastructure (AWS or Azure).
- Own code quality through reviews, testing, and sound engineering practices.
- Collaborate with data scientists, analysts, designers, and stakeholders to translate requirements into working software.
- Contribute to architectural decisions and continuous improvement of the team\'s standards and tooling.
Basic Qualifications
- Bachelor\'s or Master\'s in Computer Science, Engineering, or a related field — or equivalent practical experience.
- 3–5 years of hands-on full-stack development experience.
- Solid backend experience in Node.js and/or Python, building and integrating APIs and services.
- Strong SQL and relational database skills; comfortable with schema design and data modeling.
- Experience deploying and running applications on a major cloud platform (AWS or Azure).
- Familiarity with Git, CI/CD, and modern software engineering best practices.
- Strong problem-solving and debugging skills; effective communicator in a cross-functional team.
Preferred Qualifications
- Hands-on experience building AI/LLM-powered applications — frameworks such as LangGraph or LangChain, the MCP (Model Context Protocol), or agent/RAG architectures.
- Infrastructure-as-code (CDK, SST, Pulumi, Bicep, or Terraform) and container/serverless deployment (ECS, Lambda, Container Apps).
- Experience with serverless and edge frameworks (e.g. SST, OpenNext) and full-stack platforms like Next.js in production.
- Exposure to NoSQL, vector stores, or other AI-adjacent data infrastructure.
- Familiarity with Go or Rust.
- BI/visualization or data-product experience.
- Awareness of data governance and handling of sensitive data (PII/PHI), and compliance frameworks (SOC 2, HITRUST) — relevant for our healthcare and finance clients.