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AI Engineer with less than a year in Python, AI/ML, and RAG Pipelines.
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Assessing your cultural and operational fit
Highly motivated and results-oriented AI Engineer with a strong academic background in Computer Science and Engineering, graduating in 2026. Possessing 2 months of professional experience as a Summer Intern at Tetra Pak India Pvt. Limited, complemented by extensive project work in AI/ML, RAG pipelines, and reinforcement learning. Proficient in Python, FastAPI, PyTorch, and various AI/ML frameworks, with a proven ability to develop intelligent systems and optimize workflows.
Vellore Institute of Technology, Vellore
Bachelor of Technology · Computer Science and Engineering
September 7, 2022 – April 30, 2026
Tetra Pak India Pvt. Limited
Python Internship
May 1, 2025 – June 30, 2025
Pune, Maharashtra, India
AcuRag - Clinical Knowledge Retrieval System (RAG)
June 1, 2026 – Present
Built a RAG-powered clinical advisory platform using semantic retrieval and vector similarity search. Engineered LangChain orchestration pipelines retrieving top-5 clinically relevant guideline chunks per query using FAISS indexing. Generated structured clinical responses covering diagnosis, treatment protocols, acupuncture points, and safety considerations.
PPO-Based Multi-Agent Robot Scheduler
June 1, 2026 – Present
Designed a reinforcement learning-based scheduling engine for dynamic multi-agent robotic task allocation under constrained operational environments. Improved scheduling efficiency by 25% through reward shaping and latency-aware optimization. Built monitoring pipelines for reward convergence analysis and iterative policy tuning workflows.
Finance Tracker AI (Memory-Augmented LLM System)
June 1, 2026 – Present
Architected an LLM-powered financial intelligence system supporting automated expense categorization and semantic querying over unstructured financial datasets. Implemented persistent memory layers improving personalization accuracy by 35%. Developed preprocessing pipelines transforming raw financial records into structured JSON representations for stable inference workflows.
GitHub Analyzer MCP
June 1, 2026 – Present
Built a Model Context Protocol (MCP) server exposing GitHub profile analysis as structured AI-callable tools. Implemented recruiter-grade developer summaries, side-by-side profile comparisons, and repository intelligence endpoints. Designed for seamless integration with LLM agents and Claude-compatible AI workflows enabling automated developer evaluation pipelines.
View ProjectSAP Order-to-Cash Graph Query System (Agentic RAG)
June 1, 2026 – Present
Engineered a schema-aware Text-to-SQL platform for enterprise ERP workflows across multiple relational entities. Implemented prompt guardrails and structured context injection improving multi-table query accuracy by 30%. Reduced query latency from 5s to under 2s through DuckDB optimization and graph-aware execution pipelines.
View ProjectSaviynt Identity Security for the AI Age (ISAA)
Saviynt
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong inclination towards innovation and practical application of AI technologies, aligning well with a dynamic, project-driven AI engineering environment. The participation in hackathons and personal projects indicates self-motivation and a continuous learning mindset. The diversity of projects (GitHub analysis, finance, ERP, clinical, robotics) suggests an ability to work across different problem spaces, which is valuable for a versatile AI team. However, the limited professional experience (one internship) means there's less data to assess long-term team collaboration or corporate cultural alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and problem-solving approach, with a focus on improving efficiency and accuracy. The experience in debugging and system testing suggests an attention to detail and reliability. The diverse range of projects, from financial intelligence to clinical advisory systems and robot scheduling, demonstrates adaptability and a broad interest in applying AI to different domains. However, the lack of completed psychometric or English tests makes it difficult to fully assess work attitude, stress handling, or team collaboration skills.