Role – AI-Enabled Full Stack Developer (Build with clarity. Ship with AI)

Exp: 2+yr 

Remote Job

 

About the Role

We’re looking for a developer who thinks clearly, understands systems at an architecture level, and uses AI as a force multiplier to deliver production-quality software faster.

This is not about memorizing every framework. It’s about understanding what you want to build, knowing how systems fit together, and leveraging AI tools like Claude, Cursor, and Copilot to write, debug, test, and ship code across any stack. If you can articulate a clear requirement, design a sound workflow, and use AI to execute — you belong here.

 

What Matters Most

We evaluate candidates on three pillars:

1. Clarity of Thought & Architecture

• Ability to break down a business requirement into a clear technical plan — data models, APIs, component structure, and deployment strategy
• Strong understanding of how frontend, backend, databases, and external services connect end-to-end
• Can evaluate trade-offs: when to use REST vs. GraphQL, SQL vs. NoSQL, monolith vs. microservices
• Understands design patterns, separation of concerns, and scalable system design

2. AI-First Development Mindset

• Proficient in using AI tools (Claude, Cursor, GitHub Copilot) as core development partners — not just autocomplete
• Can write precise, effective prompts to generate, refactor, debug, and test code in any language or framework
• Knows how to validate and critically evaluate AI-generated output for correctness, security, and maintainability
• Experience integrating AI APIs (OpenAI, Claude API, etc.) into applications
• Understands prompt refinement: iterating on instructions to get production-ready results

3. Workflow & Delivery Ownership

• Comfortable with end-to-end delivery: from requirement to deployment
• Working knowledge of Git, CI/CD pipelines, and collaborative development practices
• Can manage their own workstream — prioritize, estimate, communicate blockers, and ship on time
• Writes clean, maintainable code with proper documentation and test coverage

Technical Foundation (Required)

• You should have solid experience in at least one modern full-stack combination:
• Primary Stack: MERN (MongoDB, Express, React, Node.js) — this is our core stack
• API Design: RESTful APIs and/or GraphQL
• Cloud: AWS (deployment, basic services)
• Version Control: Git (branching, PRs, code review workflows)
• JavaScript: Strong fundamentals — you should be fluent in JS/TS regardless of framework

Note: If you can build well in one stack with AI assistance, you can learn others. We care about depth over breadth.

 

Good to Have

• Python for scripting, automation, or AI/ML tasks
• Experience building LLM-powered applications (chatbots, automation tools, RAG pipelines)
• Familiarity with embeddings, vector databases (Pinecone, Weaviate, ChromaDB)
• Exposure to LAMP stack (Linux, Apache, MySQL, PHP)
• Familiarity with Angular or Vue (in addition to React)
• Basic DevOps knowledge (Docker, CI/CD, infrastructure-as-code)
• Relevant certifications in AI/ML, Generative AI, or Prompt Engineering

Key Responsibilities

• Design, develop, and maintain scalable full-stack applications on our primary stack
• Architect solutions — define data models, API contracts, and system workflows before writing code
• Leverage AI tools daily for coding, testing, debugging, and code review to accelerate delivery
• Build AI-powered features: chatbots, intelligent automation, document processing workflows
• Write and refine prompts to produce reliable, production-quality outputs from AI tools
• Ensure code quality, security best practices, and comprehensive test coverage
• Collaborate with the team on technical decisions, code reviews, and knowledge sharing
• Stay current with AI developments and continuously improve team workflows

The Right Fit

You’re someone who:

• Thinks before coding — you plan the architecture, then use AI to build it faster
• Is curious about AI and sees it as a genuine productivity multiplier, not a novelty
• Takes ownership of delivery, not just tasks
• Communicates clearly — with the team and with AI tools
• Focuses on outcomes over frameworks: the goal is to deliver working software, not to collect tool badges