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Full Stack Engineer

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Description

We're looking for a Full-Stack Engineer who's comfortable owning a feature from idea to production: designing the data model, building the API, and shipping a polished UI. You'll work closely with product, design, and our AI engineering team to bring new capabilities to life across the stack.


Responsibilities:

  • Design, build, and ship features across the full stack — from database schema and backend services to frontend UI.
  • Build and maintain RESTful APIs that power our web application and integrations.
  • Develop responsive, accessible, and performant user interfaces using modern frontend frameworks.
  • Collaborate with product and design to turn requirements into technical specs and shippable increments.
  • Write clean, well-tested, maintainable code, and participate actively in code review.
  • Improve application performance, reliability, and security across the stack.
  • Work with our AI engineering team to integrate AI-powered features into user-facing product surfaces.
  • Contribute to architecture decisions, tooling, and engineering best practices as the team and product scale.
  • Monitor, debug, and resolve production issues, and contribute to on-call rotations as needed.


Requirements:

  • 5+ years of professional experience building full-stack web applications in production.
  • Strong frontend skills: TypeScript and React, with experience building production-grade UIs.
  • Strong backend skills: Python (FastAPI, Django, or similar), with experience designing and building APIs and services.
  • Practical experience designing and working with relational databases (PostgreSQL, MySQL) and writing efficient queries.
  • Experience building and consuming REST APIs.
  • Experience integrating AI/LLM-powered features into a product — calling LLM APIs, working with retrieval-augmented generation (RAG) or vector search, or partnering with ML/AI teams to ship model-backed functionality.
  • Familiarity with cloud infrastructure (Azure, AWS, or GCP), CI/CD pipelines, and containerization (Docker).
  • Strong understanding of software engineering fundamentals: testing, version control, code review, and system design.
  • Proficiency working with AI coding assistants (e. g., Claude Code, GitHub Copilot, Cursor) to accelerate development, while critically reviewing and validating AI-generated code.
  • Comfort working in a remote, async-first environment with strong written communication skills.


Nice to Have:

  • Familiarity with infrastructure-as-code (Terraform) and observability tooling (Datadog, Grafana, Sentry).
  • Familiarity with vector databases or embedding-based search for AI-powered features.
  • Background working in a startup or small, cross-functional team.
  • Exposure to design systems and component libraries.

Skills

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