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AI Engineer with 7+ years in Python, AI/ML & Scalable Backend Systems
Nearly 6 years of expertise in software development, specializing in Python development, AI/ML, and scalable backend systems, specializing in high-performance architectures using Django, FastAPI, Flask, and asynchronous task queues (Celery). Strong background in large language models (LLMs), retrieval-augmented generation (RAG), AI agents, and MLOps, with hands-on experience in AI-powered chatbots, document analysis systems, and predictive modeling. Expertise in optimizing AI inference servers using Triton, quantization, and other techniques to enhance model performance and achieve scalable AI infrastructure. Expertise in designing and implementing TCP/IP servers, WebSockets, REST APIs, and FastAPI, as well as developing high-performance web servers in asynchronous environments. Proficient in DevOps technologies like Docker, Kubernetes, CI/CD, Nginx, RabbitMQ, and AWS for seamless deployment and scalability. Adept at network automation using PyATS and Cisco frameworks, database management (PostgreSQL, MySQL, ClickHouse, Redis, Elasticsearch), and developing secure, efficient AI & ML solutions with a focus on RAG pipelines, agentic workflows, and AI evaluation frameworks (DeepEval). Key achievements include successfully building and deploying an AI chatbot serving over 20,000 users, significantly enhancing operational efficiency and user engagement. Advanced knowledge of AI methodologies, including quantization and model optimization, ensuring the delivery of high-performance AI solutions tailored to business needs. Recognized for problem-solving skills, translating complex technical concepts into actionable strategies, fostering innovation, and driving continuous improvement within development teams. Actively mentor junior developers, sharing best practices in AI and software engineering, contributing to a skilled, collaborative, and high-performing team environment.
Jeppiaar Engineering College, Anna University
B.E. · Computer Science Engineering
August 1, 2015 – June 30, 2019
Tata Communications Limited
Technical Lead
March 1, 2022 – Present
Chennai, Tamil Nadu, India
HCL Technologies
Senior Software Developer
December 1, 2020 – March 1, 2022
Chennai, Tamil Nadu, India
Amiga IT Technologies
Python Developer
May 1, 2019 – August 1, 2020
Chennai, Tamil Nadu, India
DDoS Detection
March 1, 2022 – June 1, 2026
Developing a ClickHouse Cluster on Kubernetes with horizontal/vertical scalability. Implementing fault tolerance, shared storage systems, security, logging, and monitoring for enhanced system reliability. Migrating data pipelines to ClickHouse, achieving significant improvements in storage and retrieval efficiency.
CDN Bot Detection
March 1, 2022 – June 1, 2026
Designing data pipelines to ingest live data from Elasticsearch and store results in ClickHouse and MySQL. Developing prediction models using Random Forest to classify bot vs. human requests. Containerizing and deploying solutions as Kubernetes pods for scalability and maintainability.
LLM Deployment with Inference Server
March 1, 2022 – June 1, 2026
Researching and deploying NVIDIA Triton Inference Server for concurrent batch processing and CUDA acceleration. Implementing LLM quantization techniques to enhance model performance and reduce computational load. Dockerizing and deploying inference pipelines for efficient AI processing.
In-House AI Assistant
March 1, 2022 – June 1, 2026
Developing an AI-powered chatbot for 20,000+ employees with document summarization, Q&A, meeting minutes generation, web search integration, and data visualization. Building a Retrieval-Augmented Generation (RAG) pipeline with vector search, embedding, chunking, LLM querying, and security guardrails. Integrating Agentic RAG (LangGraph) and evaluation pipeline (DeepEval) for enhanced AI-driven automation. Architecting the solution using FastAPI + ReactJS and deploying on Kubernetes.
No-Code Bot Building Framework
March 1, 2022 – June 1, 2026
Developing a One-Click RAG Bot Deployment framework, enabling teams to deploy AI-powered bots efficiently. Building modular pipelines for data ingestion, retrieval, security, guardrails, and evaluation. Optimizing processing time using asynchronous parallel workflows. Ensuring a fully containerized and scalable deployment for enterprise-wide accessibility.
Smart Python Wrapper (Network Automation)
December 1, 2020 – March 1, 2022
Automating Cisco Network Testing using PyATS, HLtAPI, and ATS frameworks to enhance test efficiency. Migrating legacy TCL scripts to Python automation, reducing manual intervention and increasing reliability. Developing and maintaining test automation scripts for network devices, ensuring seamless integration and performance validation.
Fleet Management System
May 1, 2019 – August 1, 2020
Building a high-performance TCP server using the Twisted framework, capable of handling 100K+ simultaneous GPS tracking connections. Developing a Django-based web application with REST APIs, WebSockets, and Celery task queues for real-time data processing. Designing a real-time tracking system leveraging PostgreSQL, Redis, and RabbitMQ for optimized performance. Implementing geofencing, route tracking, invoicing, and user management functionalities to enhance system capabilities.
Cultural Fit Analysis
The candidate's project diversity, ranging from DDoS detection and CDN bot detection to LLM deployment and in-house AI assistants, indicates a broad interest and adaptability to various technical challenges. The experience across different companies (Tata Communications, HCL Technologies, Amiga IT Technologies) and roles (Python Developer, Senior Software Developer, Technical Lead) suggests an ability to integrate into different team structures and contribute effectively. The focus on AI-driven solutions and scalable architectures aligns well with an innovative and growth-oriented culture.
Soft Skills & Operational Fit
The candidate's resume highlights soft skills such as Collaborator, Communicator, Problem Solving, Analytical, and Critical Thinking. These skills are essential for a senior role, particularly in an AI engineering context where complex problem-solving and cross-functional collaboration are frequent. The experience as a Technical Lead further supports operational fit, demonstrating the ability to define strategies, set roadmaps, and mentor teams.