Mitul K.

9+ AI systems (LLM agents, RAG pipelines and AI-powered SaaS) shipped to production across SaaS, e-commerce, healthcare and real estate. Built for real users and real data, not demos. Top Rated Plus · 12+ years in software · 14,000+ Upwork hours · $400K+ earned · 149 completed jobs Most AI projects stall somewhere between a working prototype and a dependable product. The gap is usually engineering: data pipelines, permissions, evaluation, cost control and integrations. That is where my 12 years of backend, full-stack and cloud work matters. I design the AI layer and also build the system around it. AI AGENTS & AUTOMATION - Multi-agent workflows with LangGraph, LangChain, CrewAI and custom orchestration - Tool calling, memory, planning and human-in-the-loop review - MCP servers that connect Claude and other LLMs to your data and tools - Agentic automation for slow, manual business processes LLM & RAG APPLICATIONS - RAG pipelines: chunking, hybrid search, reranking, source citations - Vector databases: pgvector, Pinecone, FAISS, Qdrant - AI chatbots, copilots and internal knowledge assistants - Document intelligence and structured data extraction - Natural-language-to-SQL and analytics assistants - Evaluation, guardrails and structured outputs to reduce hallucinations MODELS & FRAMEWORKS - OpenAI, Claude (Anthropic), Gemini, AWS Bedrock, Llama, Mistral - LangChain, LangGraph, LlamaIndex - TensorFlow, PyTorch, scikit-learn when classic ML fits better than an LLM PRODUCTION BACKEND & CLOUD - Python (FastAPI, Django) and Node.js services for AI workloads - PostgreSQL, MongoDB, Redis, Supabase - AWS (Bedrock, Lambda, ECS, S3, RDS), Docker, Kubernetes, CI/CD - Auth, RBAC, logging, monitoring, latency and cost optimization - Next.js / React front ends, so one engineer can take you from model to UI I'M A GOOD FIT IF YOU NEED TO - Turn an AI idea into a deployable product - Add AI features to an existing SaaS platform - Make an unstable AI prototype production-ready - Replace a manual workflow with an AI agent HOW I WORK 1. Start from the business problem, not the model. Sometimes rules or a simple ML model beat an LLM. 2. Agree on architecture, scope and estimate before writing code. 3. Ship in small, reviewable increments with regular demos. 4. Measure quality with evaluation sets, latency and cost per request. 5. Stay on after launch for monitoring and iteration. Daily updates over Slack, Teams or Discord, with working-hour overlap for US, UK and EU teams. Tell me briefly what you're building or which process you want to automate, and I'll suggest the most practical way to approach it. Together, let's create a great product. 💌 Feel free to invite me to your job post or book a consultation today! Let's achieve your business 🎯 goals together.