I'm Archit Gupta, an AI Systems Engineer building multi-agent runtimes, memory/RAG infrastructure, and self-hosted AI systems. At Robynn AI, I work on production agent workflows and the tooling that makes them reliable: orchestration APIs, structured-output pipelines, long-running runtimes, and observability.
Building production agentic systems, self-hosted inference, and reusable workflow infrastructure
AI Systems Engineer | September 2025 - Present
Building a production agentic AI platform across a SvelteKit application and Python/LangGraph backend, including a multi-agent registry, 60+ tools, typed MCP workflows, Graphlit-backed memory, long-running execution, and observability.
Personal Systems | Ongoing
Running a home-server AI stack around a repurposed Tesla P40 and a self-hosted 16-agent system, with a custom priority queue keeping embeddings, memory, search, and RAG traffic responsive under load.
A four-agent continuous learning stock market-intelligence system that runs daily across hundreds of equities linked to dozens of commodity categories, translating macro and commodity shifts into trade-oriented research and signals.
A fine-tuned multimodal pool-strategy agent that reconstructs table layouts from photos, grounds decisions in a large billiards-specific RAG knowledge base, and recommends shot sequences tailored to player ability, style, and evolving preferences.
A compact Node.js priority-queue proxy for a self-hosted 16-agent system on a single GPU, built to keep embeddings, memory, search, and RAG pipelines responsive under real load.
League-management software for competitive billiards with real-time match tracking, ELO-based ratings across 50k+ historical matches, cryptocurrency payouts for 600+ active players, and operational tooling for league workflows.
Built an LLM-based hiring workflow that parsed resumes, generated role-specific technical questions, and automated first-pass screening; won the LabLab AI hackathon and earned incubator interest.
I'm an AI Systems Engineer based in Boulder, Colorado, focused on multi-agent runtimes, memory/RAG systems, and self-hosted or cloud-native AI infrastructure. At Robynn AI, I build production agent workflows and the systems around them: orchestration APIs, structured-output pipelines, long-running runtimes, and observability.
My background spans enterprise engineering at Cisco, PayPal, and Riverbed, plus independent contract work building hiring workflows, operational systems, and billiards-league software. I studied Computer Science and Astronomy at the University of Illinois Urbana-Champaign.
During my time at UIUC, I worked on cybersecurity infrastructure, configuring ExaBGP-based blocking and prototyping Google Rapid Response integration for incident response workflows.
Outside of tech, I play pool competitively, build AI systems around the game, and perform Indian classical music on the Sarod.
Have a project in mind or want to chat about AI? I'd love to hear from you.
