---
title: "Mayank Aggarwal - Software Engineer 2 in Greater Delhi Area | Tal"
description: "Meet Mayank Aggarwal, Senior Generative AI & Backend Engineer | Python | FastAPI | Java | Spring Boot | Agentic AI | RAG | LangGraph | Kubernetes | AWS based in Greater Delhi Area. AI stack includes antigravity, cursor, and opencode."
image: "https://tal.club/meet/mayank-aggarwal-1/share-image"
---

# Mayank Aggarwal on Tal

## Headline

Senior Generative AI & Backend Engineer \| Python \| FastAPI \| Java \| Spring Boot \| Agentic AI \| RAG \| LangGraph \| Kubernetes \| AWS

## About

Generative AI Fullstack Engineer with 6\+ years of experience building scalable backend systems, distributed applications, cloud\-native platforms, and AI\-powered production systems\. • Production AI & Enterprise Systems Recently, I've been architecting production RAG pipelines, document intelligence platforms, and Agentic AI applications for large\-scale financial documents\. I designed a hybrid retrieval pipeline that reduced financial special\-item extraction time from \~15 minutes to \~30 seconds \(\~97% faster\) using contextual keyword filtering, policy\-guided LLM inference, and targeted retrieval\. • Backend Engineering & System Design Designed high\-performance backend systems including a 100,000\+ rule validation pipeline, a DAG\-based calculation framework that reduced recalculation time from \~5 minutes to \~6–7 seconds \(43× faster\), and optimized database performance through indexing and caching\. I enjoy solving complex engineering challenges involving distributed systems, performance optimization, clean architecture, and cloud\-native applications\. Built and deployed multiple production\-grade AI applications including: • Multi\-agent AI Blog Generation System using LangGraph, GPT\-4\.1, Tavily Search, Gemini APIs, FastAPI, and Streamlit • CommentIQ – AI\-powered YouTube comment analytics platform for audience insights, buyer intent detection, sentiment analysis, and content idea generation • FastAPI production applications with authentication, SQLAlchemy, JWT workflows, validation pipelines, and cloud deployment 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 & 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 • LangGraph • LangChain • Agentic AI Systems • Multi\-Agent Architectures • RAG Pipelines • Prompt Engineering • OpenAI APIs • Groq APIs • Gemini APIs • Tavily Search • Semantic Search • AI Automation • LLM Workflows • Context Engineering 𝗕𝗮𝗰𝗸𝗲𝗻𝗱 & 𝗖𝗹𝗼𝘂𝗱 • Python • FastAPI • Flask • Java 8 • Spring Boot • REST APIs • Docker • Kubernetes • AWS • AWS EKS • CI/CD Pipelines 𝗗𝗮𝘁𝗮 & 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘆𝘀𝘁𝗲𝗺𝘀 • PostgreSQL • MongoDB • Redis • Apache Kafka • Prefect • Dask • ETL Pipelines I enjoy building scalable AI systems, autonomous workflows, cloud\-native applications, and production\-ready backend platforms optimized for real\-world business use cases\. Currently open to opportunities in: • Generative AI Engineering • Agentic AI Systems • Python Backend Engineering • AI Automation Platforms • LLM Application Development

## Location

Greater Delhi Area

## AI stack

antigravity

cursor

opencode

## Work experience

Software Engineer 2 at S&P Global, Feb 2023 \- Present · 3 yrs 7 mos, Gurugram, Haryana, India, · Built a RAG\-powered special\-items search system that detects special disclosures across financial filings, reducing discovery time from \~15 minutes to \~30 seconds \(\~97% faster\)\. Implemented a hybrid retrieval pipeline using regex\-based page filtering and policy\-guided LLM inference for scalable targeted extraction from PDF/HTML financial documents without full\-document processing\. · Designed and built a multi\-stage data validation pipeline executing 100,000\+ rule associations across six financial statement sections, enriched with live API\-sourced filing metadata \(industry classifications and segment data\), reducing manual data quality review from \~4 hours to \~15 minutes per filing before downstream ingestion\. · Designed and implemented an end\-to\-end derived\-field calculation framework powered by a DAG\-based dependency graph, enabling single\-click automatic calculation of all collected data items and reducing recalculation time from \~5 minutes to \~6–7 seconds \(\~43x faster\)\. · Optimized database performance through strategic table indexing and result caching, reducing redundant database queries and improving data retrieval latency by \~30% across validation and calculation workflows\. · Translated complex business requirements into scalable technical designs and delivered end\-to\-end solutions aligned with stakeholder expectations and project timelines\. · Conducted thorough code reviews and enforced clean coding and performance best practices, improving overall code quality and reducing production defects\.

Software Engineer at O4S, Feb 2022 \- Feb 2023 · 1 yr 1 mo, Gurugram, Haryana, India, • Designed and developed scalable backend product features using object\-oriented programming \(OOP\), SOLID principles, and design patterns, delivering maintainable and extensible enterprise applications\. • Built and maintained end\-to\-end RESTful APIs for microservices\-based architectures, enabling seamless integration between distributed services and improving system scalability\. • Engineered an end\-to\-end automated SKU onboarding platform that reduced customer onboarding time from \~1 hour to under 5 minutes through backend workflow automation, validation pipelines, and real\-time analytics, significantly improving operational efficiency and user experience\. • Developed cloud\-native backend services using Python \(Flask\) and deployed containerized applications on Docker, Kubernetes, and AWS EKS, supporting scalable and reliable production environments\. • Implemented asynchronous event\-driven workflows using Apache Kafka and ActiveMQ, enabling reliable inter\-service communication and high\-throughput distributed processing\. • Collaborated with cross\-functional teams to translate complex business requirements into scalable technical solutions while driving code quality through clean architecture, code reviews, and engineering best practices\.

Associate Level 2 at AVIZVA, May 2021 \- Jan 2022 · 9 mos, Gurugram, Haryana, India, 1\) Designed and developed complex backend features for enterprise healthcare web and mobile applications using Java, Spring Boot, and RESTful services, delivering scalable and maintainable solutions\. 2\) Built, deployed, and maintained applications on AWS, gaining hands\-on experience with cloud infrastructure, application deployment, and production support\. 3\) Performed end\-to\-end debugging and root cause analysis across backend services, resolving production issues and improving application stability and reliability\. 4\) Optimized existing application components and backend workflows, enhancing runtime performance and improving the overall efficiency of the platform\. 5\) Collaborated with business stakeholders to translate functional requirements into technical designs, prepared Functional Requirement Documents \(FRDs\) and Technical Design Documents \(TDDs\), and implemented API auditing to provide actionable insights into user behavior and system usage\.

Software Developer at Nokia, Jul 2020 \- May 2021 · 11 mos, Bengaluru, Karnataka, India

Student Trainee at Nokia, Jul 2019 \- Jul 2020 · 1 yr 1 mo, Greater Bengaluru Area

Subject Matter Expert at Chegg India, Jun 2018 \- Mar 2021 · 2 yrs 10 mos, India

## Education

Bachelor of Technology, c\.s\.e, CHANDIGARH UNIVERSITY

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

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