Lean Layer - Senior Full Stack Developer – AI Infrastructure
Requirements
• Enjoys owning systems end-to-end, from UI to infrastructure • Thinks in terms of systems, state, and data models—not just features • Is comfortable working with real-world complexity, edge cases, and evolving requirements • Has a strong bias toward building reliable, maintainable, and scalable systems • Understands how to integrate AI into real products, not just prototypes • Thrives in small, high-ownership environments • Can balance speed of execution with long-term system design • Strong experience with Python and React/TypeScript • Experience designing REST APIs and working with relational databases (PostgreSQL) • Familiarity with authentication systems and role-based access control • Experience with Docker, GCP (Compute Engine), and CI/CD pipelines • Experience building production systems with real data models and workflows • Experience working with LLM APIs and handling streaming responses • Background in small teams or startups with full-stack ownership • Experience with vector databases such as ChromaDB or Pinecone • Experience building Slack apps (Bolt SDK or similar) • Experience developing workflow systems or multi-tenant architectures • Experience deploying infrastructure across multiple customer cloud environments • Portfolio or examples of past full-stack or systems-level projects
Responsibilities
• Full Stack Application Development • Build and maintain React/TypeScript interfaces including dashboards, portals, and project management views • Develop real-time and collaborative features such as threaded conversations and shared workflows • Design and implement Python-based backend systems using FastAPI or Flask • Create REST APIs, relational data models, and application state management systems • Implement authentication, role-based access control, and approval workflows • AI Integration & Application Layer • Integrate LLM APIs (OpenAI, Anthropic) into production systems • Build application workflows where AI generates outputs and humans review/approve • Handle streaming responses and real-time AI interactions • Debug and optimize prompt behavior and model outputs • Design systems that combine deterministic logic with AI-driven components • Data Systems & Storage • Design and manage relational data models using PostgreSQL • Utilize Redis for caching, state management, and performance optimization • Work with vector databases (e.g., ChromaDB) for semantic search and retrieval • Integrate analytics and event tracking using platforms like BigQuery • Ensure data consistency, performance, and scalability across systems • Integrations & External Systems • Build and maintain integrations with third-party systems such as CRMs, Slack, Google Drive, and other operational tools • Design connectors that are reliable, configurable, and adaptable across deployments • Ensure integrations are robust and maintainable across different client environments • Infrastructure & Deployment • Containerize applications using Docker • Deploy and manage infrastructure on Google Cloud Platform (GCE, Compute Engine) • Build and maintain CI/CD pipelines using GitHub Actions • Design deployment systems that support isolated, per-customer environments • Ensure reliability, scalability, and repeatability of deployments across cloud environments
Benefits
• BrazilOTE (On Target Earnings) $40K – $80K • Offers Commission • Offers Bonus • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here • Haven't started interviewing • Early stage interviewing • Late stage inteviewing, close to offers • I have an offer, still exploring options • Annual Total Compensation (Base Salary + Bonus) in USD • Python (FastAPI / Flask) • React / TypeScript • Docker / containerized deployments • GCP (Compute Engine, Cloud CLI) • CI/CD (GitHub Actions or similar) • REST API design & auth flows • LLM API integration (Anthropic, OpenAI) • Vector databases (ChromaDB, Pinecone) • Slack app development • Multi-tenant / workflow systems • BigQuery or similar analytics warehouses • Terraform / IaC • Describe a system you built end-to-end, from data model to UI. What were the core entities, how did they relate, and what was the hardest edge case you had to deal with? • Walk us through a deployment you managed across environments. What broke, and what did you change to make it more reliable? • Please record a brief video using loom to share why you are interested in this position and what you believe makes you a strong match for the role. • We believe the best interviews are genuine conversations, and that means speaking for yourself. To ensure a fair and accurate assessment for all candidates, please refrain from using AI tools or assistants during any part of our interview process, unless given explicit direction by the hiring team. We're interested in how you approach problems, communicate ideas, and draw on your own experience. Candidates whose responses appear to rely on AI-generated content may be removed from consideration. • I agree to complete the interview process without the use of AI
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