AI & Machine Learning · Gurgaon, India
Hire a RAG Systems Engineer in Gurgaon
I build enterprise Retrieval-Augmented Generation (RAG) pipelines that turn fragmented company documentation into accurate, hallucination-resistant knowledge bases. Utilizing Supabase pgvector, hybrid search, and semantic re-ranking, I deliver high-precision enterprise AI.
Gurgaon is home to India’s leading corporate headquarters and well-funded tech unicorns. The standard here is enterprise-grade security, pixel-perfect UI, and zero-downtime deployments for consumer-facing apps. Based in India myself, there is zero timezone friction — real-time collaboration during IST business hours, rapid iteration cycles, and rates that stretch your budget further than Western contractors.
RAGpgvectorEmbeddingsSupabasePython
Ready to hire
Proof — shipped systems
- FluxDialFounder & Lead Architect — An agent-first voice-calling CRM for phone-first businesses in India and Nigeria — built because wrapping US voice APIs does not survive local telecaller math.
- MandiPeTechnical Co-Founder — Web dashboard for suppliers and delivery ops, paired with a customer Android app on Google Play — built as technical co-founder, not as a throwaway marketing site.
- RonronLead Backend & AI Engineer — A predictive real estate CRM where automations, live connections, and Postgres-backed workflows do the heavy lifting — led from the backend and AI side for an external product team.
- Divine Care IndustriesLead Engineer — Web & Android — An industrial B2B dashboard CRM with realtime catalogue indexing and order management — plus a native companion Android app on Google Play — shipped for an external industrial brand.
FAQ
- Do you work with Gurgaon-based companies?
- Yes. I work remotely and have delivered for clients in India and internationally. Whether you are a startup or an established business in Gurgaon, the engagement process is the same — email a brief, fit call, then scoped milestones.
- What does a typical rag & vector database engineer engagement look like?
- It starts with a fit call to understand scope, then a written build plan with milestones. You see working software weekly — not slideshows. Most engagements land between 2-12 weeks depending on complexity. Technologies I typically use include RAG, pgvector, Embeddings, Supabase.
- What are your rates for rag & vector database engineer work?
- Rates depend on scope, complexity, and timeline. I price by project milestone (not hourly) so you know exactly what you are paying for. Email mailtanish.me@gmail.com with your brief for a scoped estimate.
- Can you show examples of your rag & vector database engineer work?
- Yes. Check the case studies on this page — each links to a detailed breakdown of the architecture, challenges, and outcomes. I have shipped 2+ production systems in this domain.