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AI Engineer with less than a year in LangChain & Machine Learning
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Final-year CSE student specializing in AI and full-stack development, with hands-on experience building RAG pipelines, LLM-integrated platforms, and deep learning classifiers. Skilled in LangChain, PyTorch, FAISS, and production-grade MERN deployments with Redis and Docker. Strong DSA foundation with 400+ problems solved — looking to contribute to AI engineering teams building at scale.
Indian Institute Of Information Technology, Sri City
BTech · Computer Science Engineering
August 1, 2022 – June 30, 2026
IIIT Sri City Research Lab
AI-Python Intern
June 1, 2025 – July 1, 2025
Sūlūru, Andhra Pradesh, India
AI Quiz Platform
June 27, 2026 – Present
Built a PDF-to-quiz pipeline using Groq LLM SDK (Llama-3.1) to auto-generate structured question sets from uploaded course material, with a teacher-review gate before publish - eliminating manual quiz authoring overhead. Reduced API latency by 50% via a multi-key Redis caching layer with event-driven cache invalidation on quiz creation and submission events, preventing stale data without sacrificing read performance. Standardized the full deployment stack by orchestrating 4 containerized services (React, Node.js, MongoDB, Redis) via Docker Compose, securing routes with JWT in HTTP-only cookies, and enforcing API contracts via Swagger.
View ProjectAI Code Coach
June 27, 2026 – Present
Solved context-loss in generic LLM assistants by building a RAG pipeline with Python AST-aware chunking (splitting at class/function boundaries) and a persisted FAISS vector index, enabling semantically grounded code retrieval without re-indexing on every query. Routed three developer workflows (debug, translate, explain) through task-specific LangChain prompt templates and top-5 cosine similarity retrieval via Groq's Llama-3.1, with temperature=0 enforcing deterministic outputs for code-critical tasks. Closed the human-in-the-loop gap via LLM output parsing to detect fix suggestions and auto-patch source files directly, with a Streamlit chat UI exposing session-state history and retrieved source chunks for full transparency.
View ProjectProtein Prediction Using 3D Images
June 27, 2026 – Present
Solved the resolution-loss problem of naively resizing 1600x1600 protein images by designing a 9-patch spatial sampling strategy that preserves sub-structural detail, feeding patch-aggregated features into a fine-tuned ResNet-50 backbone. Achieved 83% accuracy on a 7,000+ image dataset across SARS-CoV-2, HIV, Dengue, and Ebola proteins via hierarchical multi-task learning simultaneous virus-type and protein-subclass classification on a shared feature extractor. Enabled training on constrained GPU hardware via patch-based DataLoader on T4 GPUs with Cosine Annealing WarmRestarts scheduling and gradual layer unfreezing for stable convergence on a high-resolution medical imaging task.
View ProjectOracle Cloud Infrastructure 2025 Certified AI Foundations Associate
Oracle
June 1, 2026 – Present
Azure Cloud Infrastructure Specialist
Microsoft
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from AI Code Coach to Protein Prediction, showcases a broad interest in applying AI across different domains. Their involvement in competitive programming and academic achievements indicates a drive for continuous improvement and a strong work ethic. The internship experience in a research lab aligns well with an innovative and learning-oriented culture, making them a good fit for roles requiring continuous skill development and problem-solving.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving abilities, a proactive approach to learning new technologies, and an ability to work on complex, multi-faceted projects. Their experience as a Team Lead suggests leadership potential and an understanding of task delegation and technical delivery. The detailed project descriptions indicate good communication of technical concepts and outcomes.