Gaurav K.

I build and ship production-ready AI applications — from LLM integrations and AI agents to scalable backends and complete user-facing products. I’m a Full-Stack AI Engineer with strong experience building backend systems, AI-powered workflows, and developer-facing products. I work across TypeScript, Python, Node.js, NestJS, PostgreSQL, React, OpenAI, Claude, LangChain, LangGraph, RAG, and AI agents. My strength is not just connecting an LLM to an API. I build the engineering infrastructure around AI that makes products reliable, scalable, and useful in production. AI & LLM Engineering OpenAI & Anthropic Claude integrations GPT-4 and modern LLM APIs AI agents and agentic workflows Tool/function calling and structured outputs File operations, command execution, tool orchestration, and output parsing LangChain & LangGraph RAG pipelines and vector databases Prompt engineering and prompt optimization Versioned prompt/rules management LLM abstraction layers and dynamic model switching Model evaluation, experimentation, and A/B testing Streaming LLM responses Context management and multi-step AI workflows AI-powered automation and workflow orchestration Full-Stack Engineering Backend: Node.js, NestJS, Express, Python, FastAPI, REST APIs Frontend: React, TypeScript, modern API-driven applications Data & Infrastructure: PostgreSQL, MongoDB, Redis, Meilisearch, Docker, Kubernetes Cloud & DevOps: AWS, Azure, GCP, CI/CD, Infrastructure-as-Code Integrations: Stripe, webhooks, OAuth, calendar integrations, third-party APIs What I Can Build Whether you have an early AI product or an existing application that needs AI capabilities, I can help with: → Building an AI-powered SaaS from scratch → Integrating OpenAI or Claude into an existing product → Designing and implementing AI agents → Building RAG and knowledge-base systems → Connecting agents to tools, APIs, files, databases, and external services → Developing AI copilots and developer tools → Building scalable NestJS/Node.js or Python backends → Creating React + TypeScript frontends for AI products → Designing LLM infrastructure with multiple model providers → Improving AI response quality, latency, and reliability → Taking an AI prototype into a production-ready system Why clients work with me I think beyond the API call. For AI products, I pay attention to architecture, latency, reliability, observability, prompt consistency, model abstraction, security, database design, and production deployment — because those are the things that become important once an AI prototype starts getting real users. I communicate clearly, give realistic estimates, and prefer small, testable increments rather than disappearing for weeks and returning with a large untested implementation. If you’re building an AI product and need an engineer who can handle both the AI layer and the underlying product engineering, send me a message.