Fullstack AI Engineer

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