Headline

AI Engineer (S.E @MAQ Software) | LLM Systems · RAG · Agentic Pipelines | Ex-Cybersecurity | NSUT ’26 | Open to AI/FDE Roles

About

I build AI systems — from LLM pipelines to agentic workflows — that solve real engineering problems. Currently an SDE Intern at MAQ Software, where I work on production-grade AI features used by enterprise clients. Before this, I built AI solutions at Tech Swarm and did hands-on penetration testing at CDAC — which means I think about both what systems can do and how they can break. ───────────────────────────── WHAT I BUILD ───────────────────────────── → LLM-powered pipelines (RAG, embeddings, retrieval systems) → Agentic workflows with tool use and memory → Data pipelines for ML-ready datasets → Secure-by-default AI integrations ───────────────────────────── MY EDGE ───────────────────────────── Most AI engineers understand models. I understand systems. My background in cybersecurity means I build AI that's not just functional — it's robust. I've gone from exploiting vulnerabilities to building the systems that need to resist them. ───────────────────────────── CURRENT FOCUS ───────────────────────────── → Deepening expertise in multi-agent systems & LLM deployment → Contributing to open-source AI tooling → Actively exploring: AI Engineer / Applied AI / FDE roles at AI-first companies post-graduation (July 2026) ───────────────────────────── Let's connect if you're building with LLMs, working on frontier AI products, or looking for someone who ships. ─────────────────────────────

Location

Kota

AI stack

hugging face

langchain

langgraph

openai

Work experience

Software Engineer at MAQ Software, Jan 2026 - Present · 7 mos, Noida, Uttar Pradesh, India, • Engineered an AI-driven Azure DevOps management system for autonomous work item generation. • Developed predictive machine learning models to forecast sprint delays and operational bottlenecks. • Created a scalable multi-agent automation system for 1,800 users, enhancing admin management efficiency. • Automated large-scale data scraping with the "EnergyAgentTool," ensuring high data integrity for operational intelligence.

AI Intern at Tech Swarm, Jul 2025 - Sep 2025 · 3 mos, Delhi, India, - Built an end-to-end YouTube data extraction pipeline for B2B lead generation — ingesting product + company inputs, using an LLM to auto-generate targeted search keywords, and scraping YouTube at scale to surface relevant video signals - Engineered a Z-score statistical filtering layer that eliminated 86% of low-quality/irrelevant videos before any transcript processing — cutting LLM API costs and compute overhead dramatically while keeping the pipeline scalable - Designed a two-stage LLM processing system: first pass for keyword-driven video discovery, second pass for deep transcript analysis to produce a standardized "relevance score" — transforming noisy, unstructured video data into a clean, machine-readable signal - Relevance scores were integrated directly into the company's lead scoring engine, improving B2B lead quality and accuracy for end customers

Penetration Tester at CDAC,Noida, Sep 2024 - Oct 2024 · 2 mos

Penetration Tester at CDAC,Noida, Sep 2024 - Oct 2024 · 2 mos

Logistics Coordinator at Moksha NSUT, Feb 2024 - Mar 2024 · 2 mos, Delhi, India, - Coordinated logistics for 50000+ attendee college fest, managing 12 member volunteer team - Streamlined vendor communication and scheduling, ensuring zero-delay execution across 20 + events

Subject Matter Expert at PW (PhysicsWallah), Aug 2023 - Mar 2024 · 8 mos

Student Mentor at PW (PhysicsWallah), Jun 2023 - Aug 2023 · 3 mos, - Created structured learning content for 1000+ students across JEE courses on PW's platform - Mentored 50+ students (Jun–Aug 2023) through doubt resolution, contributing to 40% improvement in assessment scores - Developed 10+ practice modules and problem sets adopted into PW's official curriculum

Education

Bachelor's degree, Computer Engineering, Netaji Subhas Institute of Technology

Schooling, Lawrence & Mayo Public School - India