I build AI agents and full-stack SaaS products using Python, FastAPI, React, Next.js, LangGraph, LangChain, and leading AI models.
I am a Top Rated Plus engineer with 100% Job Success, $100K+ earned, and 5,900+ hours delivered on Upwork. I have worked on AI agents, healthcare platforms, customer support automation, RAG applications, AI chatbots, document intelligence, and workflow-heavy SaaS products.
My role is not limited to prompts or model integration. I work across the complete product layer, including agent workflows, backend APIs, frontend applications, databases, authentication, integrations, permissions, and cloud deployment.
Before recommending an AI solution, I first understand the users, existing workflow, available data, integrations, security needs, and the business result the system should achieve. This helps determine whether the right solution is an AI agent, multi-agent workflow, RAG system, internal assistant, conventional automation, or a simpler software feature.
What I can help you build:
My core technology stack includes:
Python, FastAPI, Django, React, Next.js, TypeScript, JavaScript, LangGraph, LangChain, OpenAI, Azure OpenAI, Claude, Gemini, PostgreSQL, MongoDB, Redis, Pinecone, Qdrant, pgvector, REST APIs, GraphQL, AWS, Azure, GCP, Docker, and CI/CD.
I have worked across healthcare, customer support, fintech, real estate, data analytics, productivity, and enterprise workflow products. My focus is always on building systems that are practical, secure, scalable, and useful in real business operations.
I am a good fit when you need someone who can take ownership of the complete AI product, from understanding the workflow and planning the architecture to building the backend, frontend, agent logic, integrations, and deployment.
Jay G. earns an estimated $5.9k/mo. That's 4× the typical freelancer and more than 99.63% of everyone we track.
Have an AI agent, SaaS product, or existing workflow that you want to improve? Let’s start with a short discovery call to review your goals, current system, data, and integrations, and map the most practical first milestone.