---
title: "Sagnik Chakraborty - AI/ML Engineer in Bengaluru | Tal"
description: "Meet Sagnik Chakraborty, Agentic AI Engineer @ Reliance Intelligence | LLM Agent Orchestration · Multilingual Voice AI (Indic) · RAG · LLMOps | Ex-Amazon · Walmart | Open to relocation based in Bengaluru. AI stack includes claude code, cursor, and hugging face."
image: "https://tal.club/meet/sagnik-chakraborty-1/share-image"
---

# Sagnik Chakraborty on Tal

## Headline

Agentic AI Engineer @ Reliance Intelligence \| LLM Agent Orchestration · Multilingual Voice AI \(Indic\) · RAG · LLMOps \| Ex\-Amazon · Walmart \| Open to relocation

## About

I build production agentic AI systems: the orchestration harness, tool calling, failure recovery, memory and evals that make LLM agents fast and reliable for real users\. Most recently I am on the agentic orchestration team behind BharatIQ, Jio’s multimodal, multilingual AI assistant \(friends\-and\-family beta, tens of thousands of users\)\. There I built a deterministic fast path that cut tool\-triggered responses from 20–90s to \~1s\. I also built fault\-tolerant turn recovery so text and voice answers are never silent, dual\-channel voice streaming for code\-mixed Hindi–English \(Hinglish\), agent evals using golden sets and LLM\-as\-judge, and per\-query LLM cost attribution and quotas\. This sits on 7 years of software engineering at Amazon, Dremio \(upstream Apache Arrow / Gandiva commits\), Walmart Global Tech and a founding\-team startup, covering distributed systems, workflow orchestration \(Temporal\) and query engines\. At Walmart I shipped my first production LLM system, a RAG on\-call assistant that auto\-diagnosed \~85% of frequent alerts\. What I work on: • Agent orchestration & custom harness design · tool/function calling · MCP · semantic skill routing • Multimodal & multilingual voice agents · TTS/SSML · ASR · Indic languages & code\-mixing • RAG · embeddings · Qdrant · Pinecone · re\-ranking · guardrails • Agent evals · golden datasets · LLM\-as\-a\-judge · model benchmarking \(GPT\-5, Gemini, Claude\) • LLMOps · LLM gateways · cost attribution · latency \(P50–P99, TTFT\) · OpenTelemetry · Langfuse • Python · FastAPI · LangGraph · LangChain · Google ADK · GCP · AWS · Kubernetes Open to Agentic AI Engineer, AI Engineer and LLM Engineer roles \(full\-time, contract or part\-time\) in India, Europe and beyond\. Open to relocation\. Contact: sagnik31@gmail\.com · github\.com/sagnik31

## Location

Bengaluru

## AI stack

claude code

cursor

hugging face

mcp

Google ADK

Qdrant

## Work experience

AI/ML Engineer at Reliance Intelligence, Mar 2026 \- Present · 9 mos, Bengaluru, Karnataka, India, JioBharatIQ \- Jio’s multimodal, multilingual AI assistant \(pre\-launch; friends\-and\-family beta with tens of thousands of users\)\. Consultant on the agentic orchestration team, building core components of the custom agent harness\. • Deterministic fast path: app\-action taps and predefined triggers call the bound tool directly with zero LLM inference, cutting those responses from 20–90s to \~1s; circuit\-breaker fallback to the full agent loop; feature\-flagged, cross\-team rollout\. • Fault\-tolerant turn recovery: forced fallbacks on failed tool calls, degraded\-mode answers on timeouts, a never\-silent voice safety net, and async background completion with an “answer ready” push when users leave mid\-response\. • Multilingual voice: one streamed LLM response feeds both spoken TTS and the on\-screen answer, with provider\-specific SSML \(ElevenLabs, Google Chirp\) for Hindi, English and Hinglish\. • Agent evals & benchmarking: golden datasets and LLM\-as\-judge scoring response quality plus skill\-routing and tool\-calling accuracy over a Qdrant skill registry; GPT\-5 vs Gemini \(Vertex AI\) latency and quality benchmarks that informed the production model migration\. • LLMOps: per\-query cost attribution through the LLM gateway \(fixed \~2\.2x token under\-counting on tool turns\), per\-user quota design, \~100x smaller maps\-tool payload \(271K → 3K tokens\), provisioned\-throughput capacity audit\. • Observability & releases: OpenTelemetry, New Relic distributed tracing and AI monitoring, Langfuse tracing fixes; owned release trains v1\.13–v1\.18\. • Prototypes: Mem0 long\-term memory, MCP memory tools, Google ADK computer\-use agent, AG\-UI/A2UI generative UI streaming\.

Freelance AI & Backend Engineer at Stealth Startup, Jul 2025 \- Mar 2026 · 9 mos, Remote, • Jatayu Healthcare Technology \(VoiceDocAI\): architected B2B API\-key licensing, session\-token rotation, and real\-time concurrency and daily quota enforcement for an LLM\-powered doctor–patient transcription product, enabling third\-party HMIS integrations designed for \~1,000 concurrent users\. • Geospatial analytics: spatial population\-density pipelines \(Python, GeoPandas, Uber H3\) for radiology catchment analysis\. • Applied AI R&D: local VLM/SLM RAG prototype with retrieval\-precision and hallucination evals; agentic workflow design and self\-hosted LLM infrastructure\.

Software Engineer III at Walmart Global Tech, Dec 2023 \- Jun 2025 · 1 yr 7 mos, Bengaluru, Karnataka, India, Seller Risk platform, Walmart Global Marketplace \(fraud detection for high\-risk sellers at scale\)\. • Built an LLM\-powered on\-call assistant end to end: a RAG pipeline \(Pinecone, retrieval evaluation, layered guardrails\) in Slack that auto\-diagnosed \~85% of frequent alerts and cut manual triage \~40%\. • Engineered high\-throughput risk\-detection workflows over Marketplace seller data, publishing real\-time fraud signals to Salesforce\. • Built a BFF aggregation layer consolidating downstream risk microservices into a single API for real\-time internal dashboards\.

Senior Software Engineer at BeepKart, Feb 2022 \- Sep 2023 · 1 yr 8 mos, Bengaluru, Karnataka, India, Part of the founding team, digitising the secondhand two\-wheeler market in India\. • Shipped 3 major Java microservices from scratch, replacing legacy Magento/PHP code; improved lead generation volume by 50%\. • Implemented an end\-to\-end vehicle refurbishment workflow using Temporal \(workflow orchestration\), increasing throughput by 200%\.

Software Engineer at Dremio, 2019 \- 2021 · 2 yrs, Hyderabad, Telangana, India, Worked on the query execution team at Dremio, a data lake engine built on Apache Arrow\. • Committed upstream optimisations to open\-source Apache Arrow \(Gandiva\), improving performance of core SQL functions\. • Implemented Parquet record readers and various SQL execution operators for cloud data lake sources\.

## Education

Bachelor of Engineering \(B\.E\.\), Computer Engineering, Jadavpur University

Higher Secondary, Science, South Point High School, Kolkata

[View the original profile](https://tal.club/meet/sagnik-chakraborty-1)

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