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