---
title: "Ashwin Upadhyay - AI Engineer in Pune District | Tal"
description: "Meet Ashwin Upadhyay, AI Engineer • Lead Architect @ IRIS • Specializing in LLMOps, High-Performance RAG & Agentic Workflows (LangGraph/Kubernetes) based in Pune District. AI stack includes antigravity, claude code, and codex. Explore public work links including github, medium, and leetcode."
image: "https://tal.club/meet/ashwin-upadhyay/share-image"
---

# Ashwin Upadhyay on Tal

## Headline

AI Engineer • Lead Architect @ IRIS • Specializing in LLMOps, High\-Performance RAG & Agentic Workflows \(LangGraph/Kubernetes\)

## About

/ AI Engineer building production Generative AI, LLM, RAG, Agentic AI and AI Platform systems\. / At Sylox, I build IRIS, working across multi\-stage AI detection, LangGraph workflows, cloud integrations, secure multi\-tenancy, FastAPI/PostgreSQL and production reliability\. / Built Cerevra, a deterministic RAG engine with crash recovery and namespace isolation \-\- sub\-50ms p99 retrieval at 500\+ QPS, backed by 2,000\+ resilience and chaos tests\. / Previously built production legal\-tech RAG with hybrid retrieval, reranking and matter\-level isolation\. Also shipped 11 merged open\-source PRs across 7 projects, including Unsloth, VictoriaMetrics and Prefect\. / Python • FastAPI • LangGraph • RAG • LLMOps • pgvector • PyTorch • Kubernetes • Kafka :: I build AI systems that are reliable, secure and boring in production\.

## Location

Pune District

## AI stack

antigravity

claude code

codex

notebooklm

ollama

Pinecone

## Work experience

AI Engineer at Sylox, Feb 2026 \- Present · 7 mos, Pune District, Maharashtra, India, \\ Architected the core of IRIS, a multi\-tenant DSPM platform, shipping 44 FastAPI routers and 400\+ async REST endpoints across an 11\-schema Postgres backend\. \\ Optimized backend performance for production scale, sustaining p95 latency under 500ms at 80\-concurrency autoscale across 1M\+ records\. \\ Engineered a 7\-stage LangGraph pipeline for India\-specific PII discovery using Presidio, spaCy NER, Claude\-based verification, and custom validators, improving detection accuracy by 18%\. \\ Built 105 enterprise\-grade cloud and data\-source connectors, including SAP HANA, Snowflake, and Databricks, for large\-scale unstructured data ingestion and classification\. \\ Designed hybrid RAG infrastructure using pgvector and full\-text search, functioning as an Azure AI Search\-style retrieval layer for compliance\-focused conversational agents\. \\ Hardened platform security with OIDC/OAuth2, SCIM 2\.0, per\-endpoint RBAC, and cross\-tenant isolation for DPDP Act 2025 compliance\. \\ Owned CI/CD on GCP Cloud Build with 30\-gate verification, 161 idempotent Alembic migrations, and 80–90% diff coverage\.

AI Engineer at LOPHILS INC\., Jun 2025 \- Jan 2026 · 7 mo, Pune District, Maharashtra, India, \\ Built and shipped a production Retrieval\-Augmented Generation system with strict matter\-level namespace isolation to prevent cross\-case retrieval\. \\ Designed scalable ingestion pipelines with SHA\-256 deduplication, rich metadata extraction, and 1GB\+ large\-file streaming support\. \\ Implemented Pinecone\-based vector search using 1024\-dimensional embeddings and query\-side routing for deterministic retrieval\. \\ Developed an admin panel for namespace lifecycle management, including create, monitor, and delete workflows\. \\ Deployed end\-to\-end AI infrastructure without breaking existing n8n automation workflows\.

## Education

Bachelor of Engineering \- BE, Information Technology, Savitribai Phule Pune University \(SPPU\)

## Public links

- github: https://github\.com/wtfashwin
- medium: https://medium\.com/@wtfashwin
- leetcode: https://leetcode\.com/wtfashwin
- codeforces: https://codeforces\.com/profile/wtfashwin
- youtube\.com: https://youtube\.com/@wtfashwin
- wtfashwin\.github\.io: https://wtfashwin\.github\.io/Portfolio/

[View the original profile](https://tal.club/meet/ashwin-upadhyay)

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