vikas mandal

I'm a full-stack developer with 4+ years of production experience, specializing in Python/Django backends paired with React/Next.js frontends, and increasingly focused on LLM-powered systems and enterprise RAG pipelines (LangChain, LangGraph, vector databases).

What I'm most proud of: I built and independently operate Nyayakosh, a live legal-tech SaaS with 1,000+ users. I designed the entire pipeline solo — OCR on scanned court documents, automated bookmarking, and an LLM-powered case analysis system using RAG over a vector database, in both Hindi and English. It's not just a side project; it's a production system I own end-to-end, from infra to user support.

Day job: At Coreops.ai, an early-stage AI startup, I work on AgentCore, an ML platform for data scientists, building LLM-powered features and enterprise RAG pipelines with LangChain, LangGraph, and LangSmith. Before that, at Netweb India, I led development of Kubyts (a Docker/LXD image-repository platform) and contributed to Skylus, a private-cloud solution integrating OpenStack — so I've also got real exposure to infrastructure and cloud-scale systems, not just application code.

Why this matters for a senior role: Nyayakosh proves I can take a system from zero to production and keep it running for real users — the same technical challenges (unstructured document processing, retrieval quality, chunking strategy) that RAG-focused product teams are solving, just applied to a different domain. I'm self-taught — I moved into engineering from a non-technical role (shift manager at Starbucks) by learning Python on my own — so I care a lot about proving myself through what I've shipped rather than credentials.

What I'm looking for: A senior full-stack or GenAI/Agentic Developer role at a growth-stage company, with end-to-end ownership of production AI/RAG systems, a path toward tech lead, and a team that pushes me to keep learning. I want to avoid legacy-only maintenance or AI features that stall in a demo and never reach production.