---
title: "Poojith Mapakshi - Senior Software Engineer in Puducherry | Tal"
description: "Meet Poojith Mapakshi, Software Engineer | LLM & Backend Systems | Distributed Processing | FastAPI Celery | Python | Building scalable ML pipelines at Straive based in Puducherry. AI stack includes aistudio, antigravity, and codex."
image: "https://tal.club/meet/poojith-mapakshi/share-image"
---

# Poojith Mapakshi on Tal

## Headline

Software Engineer \| LLM & Backend Systems \| Distributed Processing \| FastAPI Celery \| Python \| Building scalable ML pipelines at Straive

## About

contact: poojithmapakshi2@gmail\.com AI/ML Engineer and Backend Developer My work is mainly on building scalable LLM systems, distributed processing workflows, and high\-reliability backend services\. I use Python, FastAPI, Celery, Redis, Spark, Databricks and common NLP and LLM tools\. I am open to roles in AI/ML Engineering, LLM systems, Backend Engineering and applied ML\. My work includes developing FastAPI\-based microservices, high\-concurrency Celery pipelines, Redis\-backed caching layers, and evaluation frameworks for numerical, entity, and factual consistency\. Technical experience spans FastAPI, Python, Celery, Redis, Spark, Databricks, PyTorch, HuggingFace, NLP workflows, distributed systems, and large\-scale text processing\. Open to roles in AI/ML Engineering, LLM Systems, Backend Engineering, NLP, and Applied ML\.

## Location

Puducherry

## AI stack

aistudio

antigravity

codex

cursor

hugging face

Figma Make

## Work experience

Senior Software Engineer at Straive Technologies, Apr 2024 \- Present · 2 yrs 5 mos, Architected scalable ML platform supporting real\-time LLM inference and production agentic workflows — owned full product lifecycle from scoping requirements to deployment and continuous iteration\. Designed and deployed multi\-agent AI system processing 800\+ documents daily; integrated Gemini 2\.5 and GPT\-4 with production safety guarantees and quality evaluation pipelines\. Championed model quality and integrity — built multi\-layer QA infrastructure \(pattern guards, entity validation, semantic verification\) achieving 95% reduction in faulty LLM outputs in production\. MLOps & SDLC best practices: Implemented CI/CD pipelines \(GitHub Actions, Docker, Kubernetes\); maintained model versioning, automated testing, and zero\-downtime deployments in production\. Drove innovation in ML scalability: Redesigned async LLM orchestration with AsyncIO and parallel Celery workers — 65% latency reduction and 60% throughput increase at zero infrastructure cost\. Production reliability: Architected fault\-tolerant system with idempotent consumers, retry mechanisms, safe fallbacks, and real\-time monitoring achieving 99% uptime under operational load\. Data infrastructure: Optimized PostgreSQL for high\-concurrency AI workloads \(connection pooling, query optimization, 40% DB load reduction\); built Redis\-backed caching and event\-driven pipelines for big data processing\.

Software Engineer at Straive, Feb 2024 \- Present · 2 yrs 7 mos, • Architected Doc Prep—an internal prompt\-engineering automation system—reducing manual structuring by 80% and scaling to 300\+ manuscripts/day • Built multi\-layer GuardRails \(numerical, proper nouns, scientific/medical terms, UK/US spelling\), and integrated QualityAgentCheck using GPT\-4o/Gemini; reduced faulty edits by 95% • Engineered high\-scale backend \+ LLM pipelines using FastAPI, Celery, Redis, async workers, and autoscaling strategies • Solved a production bottleneck caused by 80–90 redundant LLM calls per table; redesigned orchestration to cut processing time from 5–6 mins → <2 mins \(65% faster\) • Implemented text\-comparison evaluation pipelines for entity, numerical, and factual consistency—improving editorial quality by 25% • Tuned Celery concurrency \+ Redis caching to reduce latency by 40% and push reliability toward 99\.99% uptime • Built real\-time observability dashboards for latency, worker activity, queue depth, and failures

Software Engineer Intern at Straive, Feb 2024 \- Apr 2024 · 3 mos, Puducherry, India, • Improved marketing decision\-making by developing a segmentation model that increased conversions by 15% • Designed the initial prototype of Doc Prep, enabling 80% reduction in manual document structuring • Enhanced ML reliability by optimizing CI/CD for model versioning, cutting deployment time from hours to minutes

Education at Puducherry Technological University, Jun 2020 \- Aug 2024 · 4 yrs 3 mos, United Kingdom

## Education

Bachelor of Engineering, Computer Engineering, Puducherry Technological University

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

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