About

About

I build AI applications — the unglamorous part, mostly. Getting a model to produce something impressive once is easy now. Getting a system to produce something correct on the ten thousandth call, when the input is malformed and the tool times out and the user changes their mind halfway through, is where the engineering is.

At Oracle I work inside Fusion SCM Cloud on agentic and retrieval-backed workflows: a part-matching pipeline that blends fuzzy matching with semantic retrieval and a web-search fallback, an order-classification agent with rule guardrails and a human-review handoff, and RAG flows over planner exceptions and tabular data. These run against real customer data, which is a good teacher.

Outside that I work on kubeflow/docs-agent through Google Summer of Code 2026, and turn up to the Kubeflow Docs Agent community call every other Saturday to argue about where it should go next.

I'm looking for senior AI engineering work: agent platforms, inference and serving, or retrieval at a scale where the naive approach stops working.

Experience

Open source contributor, docs-agent

May 2026 — present

Kubeflow · Google Summer of Code 2026 · Remote

Expanding kubeflow/docs-agent from a documentation chatbot into an agentic RAG reference architecture for the Kubeflow project.
Built multi-index retrieval across GitHub issues, application code, Kubernetes manifests and 1,000+ Markdown pages — roughly 10,000 searchable chunks carrying path, product-area, version and source metadata.
Merged a 5.4k-line change adding a three-tool MCP server, TEI embeddings, the issues and code ingestion pipelines, and CI/CD onto OCI/OKE.
Now hardening the public edge: rate limiting, CORS lockdown and anonymous session-JWT auth, with Istio configuration migrated into a Helm chart so guardrails ship with the deployment.
Added a 71-test suite and CI workflow covering retrieval behaviour, so a regression in ranking fails the build instead of surfacing in production.

AI Application Developer

Jun 2024 — present

Oracle · Bengaluru, India

Build agentic and retrieval-backed features inside Oracle Fusion SCM Cloud across three customer-facing workflows: catalog lookup, order review and planner assistance.
Designed a part-matching pipeline combining fuzzy matching, semantic retrieval, clustering and a web-search fallback over manufacturer and retailer catalogs, lifting match coverage for asset-mapping workflows by around 30%.
Shipped an order-classification agent with batch processing, rule-evaluation guardrails, exception routing and a human-review handoff, handling 10,000+ order lines per run.
Built RAG planner-assist flows over exceptions, notes and tabular data that cut repeated manual investigation by around 40% through source-grounded answers.
Won the Oracle Gen AI Hackathon — first among 33 teams, top five among 300+ participants.

Application Developer Intern

May 2023 — Jul 2023

Oracle · Hyderabad, India

Implemented Copy Data for lead-time columns in Oracle SCM, and optimised the retrieval and update path with Elasticsearch queries and PATCH-based API updates.
Added linear-regression trend analysis to Oracle JET charts for supply-chain forecasting views.

What I work with

Agents & LLM systems

LangGraph · LangChain · MCP · Agentic RAG · Tool calling · Evals · QLoRA / LoRA · Structured output

Serving & retrieval

vLLM · SGLang · KServe · TEI · Milvus · FAISS · ChromaDB · Elasticsearch

Platform

Kubernetes · Kubeflow Pipelines · Docker · Istio · Helm · OCI / OKE · GitHub Actions

Languages & frameworks

Python · TypeScript · Java · C++ · FastAPI · Next.js · React · PostgreSQL

Selected

Selected for Google Summer of Code 2026 with Kubeflow, for an agentic RAG project.

Won the Oracle Gen AI Hackathon: 1st of 33 teams, top 5 among 300+ employees.

Runner-up, Tri-NIT Hackathon 2024, backend track.

600+ problems solved across LeetCode, GeeksforGeeks, CodeChef and Codeforces; ran 15+ competitive programming contests with student discussions.