AI Engineer with less than a year in LLM integration, RAG pipelines, and scalable architecture desig
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Final-year Computer Science (AI & ML) student with practical experience building and deploying production-grade AI/ML systems, including LLM integration, RAG pipelines, scalable architecture design, and model deployment across AWS and GCP. Skilled across the full SDLC, from API design to CI/CD and live deployment. Seeking AI Engineering, GenAI, or MLOps opportunities involving LLM applications, scalable backend systems, and production deployment.
Roorkee Institute of Technology
B.Tech · Computer Science Engineering (AI & ML)
N/A – June 30, 2026
Codebase RAG System: Semantic Code Search Engine
June 24, 2026 – Present
Built RAG system (FastAPI, Pinecone, Mistral AI, Streamlit) that returns cited answers with file path and line numbers in <5 seconds. Added self-critique agent scoring answers on three dimensions (faithfulness, relevance, completeness) and an auto-summarizer across six supported file types.
View Project270M-Parameter Transformer: Built From Scratch
June 24, 2026 – Present
Trained 270M-parameter Gemma-style transformer (GQA, RoPE, RMSNorm) in PyTorch on a ~1B-token dataset; achieved validation loss 2.3083 at ~8,000 tokens/sec on T4 GPU. Demonstrates production-level understanding of LLM internals; validates architectural choices (GQA vs MHA) for memory-efficient inference at scale.
View ProjectCodeSentinel: AI-Powered Code Vulnerability Scanner
June 24, 2026 – Present
Deployed AI vulnerability scanner (Mistral Codestral, FastAPI, SQLite, JWT auth) via model deployment on Render; scans files in under 3 seconds per request. Shipped 3 major releases adding file upload, scan history, and mobile-responsive UI; maintained 100% uptime on Render free tier.
View ProjectJobGenie AI: Full-Stack AI Career Platform
June 24, 2026 – Present
Deployed full-stack AI career platform (FastAPI, Next.js, PostgreSQL, ChromaDB) that reduced resume analysis time by ~70% using Mistral AI. Led backend architecture and Mistral AI integration in a 3-member team; delivered and presented as B.Tech major project at final viva. Resolved 3 critical production bugs (data isolation, auth 422, NaN scoring), improving interview score accuracy by ~40%.
View ProjectBeginner to Advanced MLOps on GCP (CI/CD, Kubernetes, Jenkins)
Udemy
June 1, 2026 – Present
AI Agents 101
AMD AI Academy
June 1, 2026 – Present
TensorFlow for Deep Learning Bootcamp
Udemy
June 1, 2026 – Present
AI Agents Fundamentals
Hugging Face
May 1, 2025 – Present
Introducing Generative AI with AWS
Udacity
November 1, 2024 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong interest and practical application in AI/ML, Generative AI, and MLOps, which aligns well with an AI Engineer role. The diversity of personal and academic projects (RAG systems, transformer training, vulnerability scanners, career platforms) demonstrates a broad curiosity and ability to apply AI across different domains. The certifications further reinforce a commitment to continuous learning and staying current with industry trends, indicating a good cultural fit for an innovative and growth-oriented team.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on delivering functional, scalable systems. Leading backend architecture in a team project suggests collaboration and leadership potential. The emphasis on maintaining uptime and shipping releases points to a strong operational mindset. However, without direct interview data, specific soft skills like communication under pressure or conflict resolution cannot be fully assessed.