Fullstack AI Engineer

Compensation: No equity

About the Role

We are looking for an AI Product Engineer who can transform business requirements into intuitive, scalable, and production-ready AI-powered applications.

This role requires a strong combination of full-stack engineering, modern AI integration, and product thinking. You will work closely with stakeholders, take ownership of outcomes, and build high-quality AI-driven products from concept to deployment.

We are specifically looking for confident communicators who can collaborate with stakeholders and independently drive product development.

Key Responsibilities

• Partner with stakeholders to translate business requirements into structured product designs and user experiences. Design and develop AI-powered features using LLM APIs such as OpenAI, Claude, and Gemini, including implementation of Retrieval-Augmented Generation (RAG), prompt engineering, context management, response validation, and error handling.
• Design scalable database schemas to support application data, chat histories, and embeddings, while building full-stack applications using modern frontend and backend frameworks. Rapidly prototype solutions using AI-assisted coding tools such as Cursor, Copilot, and Claude Code, ensuring all AI-generated code is reviewed and refined before production deployment.
• Deploy and maintain applications using AWS infrastructure and CI/CD pipelines, and take ownership of the complete lifecycle from design and development to deployment, monitoring, and continuous improvements.

Technical Skills Must Have

• We are looking for candidates with 3–6 years of experience in full-stack development, with a strong preference for 5+ years. The ideal candidate should have hands-on experience in backend development using Node.js or Python and frontend development using React or Angular.
• They should have practical experience in AI integration, including working with LLM APIs such as OpenAI, Claude, or Gemini, along with a strong understanding of RAG (Retrieval-Augmented Generation), prompt engineering, and context handling.
• The candidate should also have experience in PostgreSQL schema design and a good understanding of embeddings and vector databases.
• Additionally, familiarity with AWS services (EC2, S3) and CI/CD pipelines using GitHub Actions is required. Experience with AI-assisted development tools such as Cursor, Copilot, or Claude Code will be an added advantage.

Nice to Have

• Experience with AI orchestration frameworks (MCP, multi-agent systems)
• Proficiency in TypeScript, GraphQL, and Docker
• Startup or product experience (0 → 1 builds)
• Familiarity with AI observability tools (LangSmith, Helicone)

What You Bring

• Excellent communication skills (MANDATORY)
• Strong spoken and written English
• Ability to explain technical concepts to non-technical stakeholders
• Strong debugging and problem-solving skills (especially AI unpredictability)
• Ability to combine design thinking with engineering execution
• High attention to UI/UX quality and clean code
• Strong ownership mindset with accountability for outcomes
• Confidence to work independently and drive results

Values & Culture

Product Mindset Engineers think like product owners and focus on outcomes, not just tasks

Ownership End-to-end responsibility for what you build

Craftsmanship Clean architecture, thoughtful design, and scalable engineering