---
title: "Jayachandran Ramadoss - Lead Software Engineer in Chennai | Tal"
description: "Meet Jayachandran Ramadoss, Lead Software Engineer @ DevRev | Core AI · Multi-Agent Systems · Agentic RAG · Data & Analytics based in Chennai. AI stack includes claude code, codex, and kimi."
image: "https://tal.club/meet/jayachandran-ramadoss/share-image"
---

# Jayachandran Ramadoss on Tal

## Headline

Lead Software Engineer @ DevRev \| Core AI · Multi\-Agent Systems · Agentic RAG · Data & Analytics

## About

I build AI systems and data platform behind DevRev that survive production — autonomous agents, edge inference, and the large\-scale data platforms are underneath them\. Lead Software Engineer at DevRev \(Agents & Analytics\)\. On the AI side I architect production agentic systems — multi\-agent triage \(plan\-execute\-synthesize, confidence scoring, adversarial audits, MCP tool offload\) and RAG workflows shipping in internal triage\. I work end\-to\-end across the data path — MongoDB CDC, Kafka, BigQuery, Temporal ETL, DuckDB across cloud, WASM, and on\-device edge — hardening multi\-tenant SaaS that serves millions of tickets, issues, and conversations\. The rare part is the combination — cloud data platform, edge device, and the AI layer between\. I don't think AI replaces great engineers; it raises the bar for what they can do\.

## Location

Chennai

## AI stack

claude code

codex

kimi

notebooklm

obsidian

opencode

## Work experience

Lead Software Engineer at DevRev, Jul 2026 \- Present · 4 mos, Chennai, Tamil Nadu, India, I build the AI and data platform behind DevRev\. I turn core AI and large\-scale data into systems that ship and hold up in production\. Lead engineer for Agents & Analytics — the multi\-agent runtime \(orchestration, agentic RAG, core AI\) on one side, and a real\-time, multi\-tenant analytics platform on the other: CDC pipelines, Temporal ETL, and edge DuckDB handling millions of tickets, issues, and conversations across 21,000\+ organizations and 6 regions\.

Software Engineer at DevRev, Jul 2026 \- Present · 3 mo, Chennai, Software Engineer, Data Analytics \| December 2025–June 2026 Technical lead across two teams spanning agents, analytics, data foundations and workflows\. On\-device AI and model systems — Offline Edge Computer First\-place hackathon team project; direct co\-founder endorsement and equity award\. • Architected a custom on\-device agent runtime with direct llama\.cpp integration, quantized GGUF models, Metal GPU inference and Electron process isolation; implemented an Anthropic\-compatible API while keeping LLM inference and prepared\-context retrieval local\. • Engineered small\-model safeguards through serialized inference, context\-window budgeting and JSON Schema\-constrained decoding for structured tool calling, with token\-budgeted transcript trimming and validated tool selection\. • Built on\-device retrieval\-augmented generation \(RAG\) using dense embeddings, SQLite FTS5/BM25 and reciprocal rank fusion \(RRF\), grounding responses in conversation\-scoped local context\. • Designed a cloud\-to\-edge model\-adaptation pipeline combining teacher\-trace validation, knowledge distillation and LoRA\-based parameter\-efficient fine\-tuning \(PEFT\) for compact local models\. Autonomous agent systems and orchestration • Architected and engineered a multi\-agent ticket\-triage system used across 3,000\+ tickets, orchestrating specialist agents for knowledge retrieval, runtime diagnostics, source\-code investigation and engineering handoffs\. • Designed evidence\-gated orchestration with independent LLM critique, bounded investigation budgets, delta\-aware follow\-ups and controlled lesson capture, keeping customer responses as human\-reviewed drafts\. Search, agent runtimes and workflow engineering • Led feature engineering and implementation for OpenSearch\-backed Wisp hybrid search, spanning KNN/vector semantic retrieval, BM25 lexical search, weighted RRF and reranking with rank\-fusion fallback\. • Engineered agent SDK and Agent Studio capabilities for tool calling, prompt guidance, orchestration

Software Engineer at DevRev, Dec 2025 \- Jul 2026 · 8 mos, Chennai, Tamil Nadu, India, Senior engineer at the intersection of large\-scale data infrastructure, edge query engines, and agentic AI\. On DevRev's Data Analytics team I worked end\-to\-end across the whole platform; the AI\-agent and edge\-inference work I drove in parallel became my Lead charter \(Jul 2026\)\. Data platform — end\-to\-end: \- Engineered in this pipeline top to bottom: MongoDB CDC → Kafka → BigQuery → Temporal ETL → Parquet → catalog → DuckDB engines in cloud, browser \(WASM\), and on\-device edge\. \- In multi\-tenant SaaS serving millions of tickets, issues, and conversations across 6 regions, I hardened and debugged what broke: led the Edge Compute engine migration; \- Cut edge idle memory 12× via allocator\-level profiling \+ adaptive management; tuned real\-time incremental sync \+ schema evolution; hardened network resilience \(NetworkGuard, mTLS\) AI, agents & inference: \- I architected autonomous multi\-agent ticket triage — plan\-execute\-synthesize orchestration over live telemetry, with confidence scoring, adversarial audits, and MCP tool offload — and contributed across the wider ecosystem \(KYC, Lighthouse, IMA\) plus agent skills and RAG workflows used by teammates in production\. \- Where I go deepest is edge AI: I connect retrieval, memory, and inference into one local\-first system — GraphRAG/Graphify retrieval, self\-improving memory with reinforcement loops, LoRA adaptation, knowledge distillation, and quantized edge models running NL\-to\-SQL fully offline on no\-GPU laptops\. Its 4\-tier fallback is the core contract, not a safety net: DistilBERT intent → RoBERTa schema linking → constrained decoding \(SQL FSM \+ schema trie\) that prunes the output space so the model degrades gracefully instead of hallucinating\. Won 1st prize solo at DevRev's hackathon\. Stack: Go · TypeScript · Python · MongoDB · Kafka · BigQuery · Temporal · DuckDB · WASM · GraphRAG · LoRA · Knowledge Distillation · Constrained Decoding · Edge Inference · MCP

Software Engineer at ZOHO CORPORATION — MANAGEENGINE, Jul 2022 \- 2025 · 2 yrs 7 mos, Recognition: Awesome Performer \(2024\); Passionate Programmer \(2023\)\. Applied ML and predictive features • Engineered NLP features for field prediction, sentiment analysis and text classification; trained and tuned SBERT\-based field\-prediction classifiers using historical records and related\-field context\. • Designed configurable ML training and inference pipelines across portals, modules and fields, covering text preprocessing, vectorization, model\-to\-field mapping, scheduled retraining, prediction APIs and user\-feedback capture\. • Benchmarked concurrent model training and inference across portals; profiled CPU/memory behavior, diagnosed model\-reload stalls and tuned caching in load\-test environments\. Core product and systems engineering • Redesigned Java mail processing as a producer\-consumer pipeline, separating single\-threaded fetching, database\-backed staging and parallel workers for new\-mail, conversation and AI workloads\. • Led PostgreSQL upgrade and reliability work across ServiceDesk Plus and AssetExplorer, covering automated migration, backup/restore safeguards, compatibility fixes and security\-driven updates\. • Developed a configurable business\-module builder for extending ServiceDesk Plus with custom application modules\. Engineering automation • Built a configuration\-driven Java framework to install, start, restore and upgrade product instances across Windows and Linux, coordinating remote execution over WinRM and SSH with centralized status reporting\. AI integration • Built a Java\-based Model Context Protocol \(MCP\) server to expose product capabilities through a standardized interface for AI clients and tool invocation\.

Member Technical Staff at Zoho, May 2022 \- Dec 2025 · 3 yrs 8 mos, Chennai, Tamil Nadu, India, Backend & platform engineer on ManageEngine ServiceDesk Plus — a flagship enterprise ITSM product used by thousands of customers under strict SLAs\. I owned and shipped backend, database, and AI\-enabled modules across the product\. What I worked on: • AI\-enabled backend: designed SBERT\-based field prediction across 36 languages \(self\-improving retraining loop, Llama\-3/Qwen synthetic data\) and a standards\-compliant MCP server \(Java \+ Python, OpenAPI, provider\-neutral adapters for OpenAI/Claude/internal models\) — plus GPT\-based generation, classification, and summarization with hallucination controls\. • Distributed & concurrent systems: designed and improved high\-throughput mail/messaging pipelines \(POP, IMAP, EWS, Microsoft Graph\) with thread\-pool isolation, retries, and backpressure\. • Databases & reliability: owned bundled PostgreSQL end\-to\-end — zero\-downtime upgrades, performance tuning, security hardening, and live corruption recovery \(pg\_toast/FSM/VM\) on customer data\. • Identity & security: designed Login and OAuth2/JWT flows balancing security, backward compatibility, and UX\. • Platform frameworks & UI: built a custom ORM/mapper, caching, and REST/OpenAPI frameworks; delivered Ember\.js \(HBS\), JavaScript, HTML/CSS components wired to backend and AI workflows\. Impact: • \~180% higher throughput in critical mail workflows; 40% faster queries via caching \+ tuning\. • \~95% fewer recurring support issues on owned modules; 98% support rating\. • \~75% shorter test/release cycles through platform automation and tooling\. • Two internal awards — Awesome Performer \(2024\) and Passionate Programmer \(2023\) — for ownership of critical, customer\-impacting systems\. Core domains: Backend & Platform · Distributed Systems · AI/LLM Integration · PostgreSQL · Identity/OAuth · Enterprise SaaS Stack: Java · Spring · PostgreSQL · Python · REST · OpenAPI · Microservices · Java Concurrency · SBERT · ONNX · MCP · Ember\.js · OAuth2 · JWT

Summer Intern at Zoho, May 2021 \- Jun 2021 · 2 mos, Chennai, Tamil Nadu, India, \- Product Automation Tool – Java\-Based Admin–Client Automation Framework \(Internship Project\) Tech Stack: Java 11, SSH, WinRM, JSON Configurations, Multi\-OS Automation \(Windows, Ubuntu, RedHat, CentOS\), CI/CD Concepts\. \- Built an Admin–Client automation framework to remotely install, upgrade, restore backups, and manage product instances across multiple OS environments using native protocols—no external tools required\. \- Designed one\-to\-many admin–client architecture, with secure authentication and OS\-native execution \(SSH/WinRM\)\. \- Implemented process tracking, cloud file handling, and email reporting for complete visibility of operations\. \- Impact: Reduced testing effort by 75%, accelerated feature releases across environments, and automated repetitive developer workflows\.

## Education

Bachelor of Engineering, Electronics and Communications Engineering, Sri sairam engineering college

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

```json
{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Person",
      "@id": "https://tal.club/meet/jayachandran-ramadoss#person",
      "name": "Jayachandran Ramadoss",
      "url": "https://tal.club/meet/jayachandran-ramadoss",
      "image": "https://tal.club/meet/jayachandran-ramadoss/profile-photo.jpg",
      "description": "Meet Jayachandran Ramadoss, Lead Software Engineer @ DevRev | Core AI · Multi-Agent Systems · Agentic RAG · Data & Analytics based in Chennai. AI stack includes claude code, codex, and kimi.",
      "jobTitle": "Lead Software Engineer",
      "worksFor": {
        "@type": "Organization",
        "name": "DevRev"
      },
      "hasOccupation": {
        "@type": "Occupation",
        "name": "Lead Software Engineer"
      },
      "homeLocation": {
        "@type": "Place",
        "name": "Chennai"
      },
      "alumniOf": [
        {
          "@type": "EducationalOrganization",
          "name": "Sri sairam engineering college"
        }
      ],
      "knowsAbout": [
        "claude code",
        "codex",
        "kimi",
        "notebooklm",
        "obsidian",
        "opencode"
      ],
      "mainEntityOfPage": {
        "@id": "https://tal.club/meet/jayachandran-ramadoss#webpage"
      }
    },
    {
      "@type": "ProfilePage",
      "@id": "https://tal.club/meet/jayachandran-ramadoss#webpage",
      "url": "https://tal.club/meet/jayachandran-ramadoss",
      "name": "Jayachandran Ramadoss on Tal",
      "description": "Meet Jayachandran Ramadoss, Lead Software Engineer @ DevRev | Core AI · Multi-Agent Systems · Agentic RAG · Data & Analytics based in Chennai. AI stack includes claude code, codex, and kimi.",
      "dateModified": "2026-10-29T14:46:56.221Z",
      "isPartOf": {
        "@id": "https://tal.club/#website"
      },
      "mainEntity": {
        "@id": "https://tal.club/meet/jayachandran-ramadoss#person"
      },
      "primaryImageOfPage": {
        "@type": "ImageObject",
        "url": "https://tal.club/meet/jayachandran-ramadoss/profile-photo.jpg",
        "contentUrl": "https://tal.club/meet/jayachandran-ramadoss/profile-photo.jpg",
        "caption": "Jayachandran Ramadoss profile photo on Tal"
      },
      "inLanguage": "en-IN"
    }
  ]
}
```