AI-Enabled Full-Stack Engineer

About the role

We are looking for a versatile AI-Enabled Full-Stack Engineer to bridge the gap between traditional web development and modern artificial intelligence. You will own features end-to-end - from the user interface and backend APIs to LLM integration, retrieval-augmented generation (RAG), and agent workflows. This is an applied AI role focused on rapid, reliable product delivery rather than foundational model training.

Responsibilities

• End-to-End Development: Design and build scalable web features using modern frontend and backend stacks (e.g., TypeScript, React, Next.js, Python, FastAPI, Java, Spring Boot).
• Applied AI Integration: Integrate Large Language Model (LLM) APIs, vector search, and RAG architectures into production user flows.
• Agent & Tool Workflows: Build custom AI agents, manage context windows, and implement structured tool invocation or Model Context Protocol (MCP) interfaces.
• AI Reliability & Guardrails: Design for AI failure modes, latency constraints, token cost tracking, hallucination mitigation, and observability.
• AI-First UX: Collaborate with product and design teams to craft intuitive, responsive, and AI-driven user experiences.
• Production Deployment: Containerize and scale services using Docker and Kubernetes (K8s) on cloud platforms (AWS/Azure/GCP), with automated CI/CD pipelines.

Qualifications

Experience: 5+ years of professional full-stack software development experience.

Skills

• Frontend & Backend: Strong proficiency in JavaScript/TypeScript, modern UI frameworks (React, Next.js), and backend services (Node.js, Python, Java, Spring Boot).
• AI/ML Tooling: Hands-on experience integrating LLM APIs, prompt engineering, vector databases, and RAG frameworks.
• System Architecture: Solid understanding of RESTful APIs, relational/NoSQL databases, and cloud-native microservices.
• Cloud & Infrastructure: Hands-on experience with AWS and container orchestration using Kubernetes (K8s), including deploying and scaling production workloads.
• Production Mindset: Familiarity with AI observability, security guardrails, cost optimization, and evaluation metrics.