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AI Engineer with less than a year in Multi-Agent AI Systems & Full-Stack Development
Results-driven AI/ML and Full-Stack Engineer specializing in multi-agent AI systems, LangGraph agentic pipelines, and production-grade web applications. Built Vyuham, a 5-agent LLM strategy platform that compresses research-to-report time from days to minutes, and Talynzo, a full-stack job-tracking SaaS backend. Experienced in LLM-powered code review automation, cloud-native deployments, and end-to-end product delivery. Passionate about turning complex AI research into scalable, user-facing products.
Chandigarh University
B.E. · Computer Science & Engineering (Hons.) AI & ML
August 1, 2021 – June 30, 2025
Crateethiks
AIML Engineer
July 1, 2025 – Present
Bengaluru, Karnataka, India
Bharat Electronics Limited
Information Security Intern
June 1, 2023 – August 1, 2023
Panchkula, Haryana, India
Vyuham - AI Strategy Agent System
June 1, 2026 – Present
5-agent sequential pipeline (Researcher, Alignment, Assessment, Exploration, Execution) transforming a business domain into a structured strategy report with SWOT, KPI tracking, and 'Big Moves' scoring - with HITL gates at 3 stages and automated PDF/Markdown output.
View ProjectPanodo.ai - AI-Powered DevX & Code Review Platform
June 1, 2026 – Present
Full-stack AI code review platform (React + TypeScript + FastAPI) with LLM-powered semantic analysis (Ollama, Sentence Transformers, Strands agents), event-driven GitHub/GitLab/Bitbucket integrations via Webhooks + OAuth2, and containerised deployment on AWS CDK + Kubernetes + GitHub Actions CI/CD – reducing manual PR review turnaround by ~35%.
Talynzo - Job Tracking Platform Backend
June 1, 2026 – Present
Complete backend for a job-tracking SaaS: job listings, applications, candidate status tracking, recruiter management, and analytics - built for scale and reliability.
AI-Powered Video-to-Photo Frame Generator
June 1, 2026 – Present
Full-stack tool extracting curated video frames using perceptual hashing for sharp, emotion-neutral selection.
Traffic Prediction – Beyond Traffic Jams
June 1, 2026 – Present
Deep-learning traffic forecasting system using hybrid LSTM/GRU/CNN models achieving 94.6% accuracy with real-time API integration.
LangChain Early Disease Prediction App
June 1, 2026 – Present
Symptom-based disease prediction pipeline using LangChain achieving 89% diagnostic accuracy.
AI-Based Fraud Detection Dashboard
June 1, 2026 – Present
React dashboard with ML fraud scoring achieving 97.4% detection accuracy; PostgreSQL-backed risk visualisation.
Advanced Machine Learning on Google Cloud
Google Cloud
June 1, 2026 – Present
Natural Language Processing on Google Cloud
Google Cloud
June 1, 2026 – Present
Analytics for Decision Making
University of Minnesota
June 1, 2026 – Present
Intro to Data Science Specialization
IBM
June 1, 2026 – Present
Computer Vision and Image Processing
IBM
June 1, 2026 – Present
Data Warehousing and Business Intelligence
UCI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate exhibits a strong cultural fit for an AI Engineer role, particularly in an innovative and fast-paced environment. Their project portfolio is diverse, spanning academic, personal, and professional contexts, showcasing a broad interest and continuous learning. The professional projects like Vyuham and Panodo.ai demonstrate an ability to tackle complex, real-world business problems with advanced AI solutions. The breadth of technologies used (LangGraph, LLMs, RAG, Docker, Kubernetes, AWS, React, FastAPI) indicates adaptability and a willingness to explore new tools. The focus on end-to-end product delivery and measurable impact aligns well with a product-driven culture.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex AI system design (Vyuham) and practical application (Panodo.ai). Their experience with Human-in-the-Loop (HITL) systems indicates an understanding of robust, auditable AI deployments. The focus on reducing manual effort and improving efficiency (e.g., ~80% reduction in strategy prep, ~35% reduction in PR review) suggests a results-oriented and operationally aware mindset. Collaboration is implied through full-stack project delivery and integration work.