Atharva Admile
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with less than a year in Agentic AI Systems & RAG Pipelines.
Final-year CS engineer with hands-on experience building agentic AI systems - including a Model Context Protocol (MCP) server enabling autonomous tool execution by AI agents, and a RAG pipeline grounding natural language queries in live data. Built TraceLab, a healthcare-compliance AI platform validated against FDA 21 CFR Part 11 and ISO 13485 standards - direct experience in the regulated life-sciences domain. Strong Python fundamentals, hands-on LLM API integration (Google Gemini, NVIDIA NIM), and familiarity with cloud platforms (GCP, Azure). Quick learner with an ownership-driven mindset, ready to contribute to agentic supply chain orchestration in the life sciences industry.
Nutan College of Engineering and Research
B.Tech · Computer Science and Engineering (AI Specialization)
August 1, 2022 – June 30, 2026
New Arts, Commerce and Science College
HSC · Science
June 1, 2021 – May 31, 2022
Don Bosco English Medium School
SSC
June 1, 2020 – May 31, 2020
KisanSahay - Agricultural Scheme Access Platform
January 1, 2026 – January 1, 2026
Designed a deterministic decision engine with explicit guardrails – deliberately avoiding LLM-based decisions for high-stakes eligibility outcomes, demonstrating practical understanding of where agentic/LLM systems need hard constraints to prevent unreliable outputs Built a full-stack system with offline-first resilience proactive failure handling and graceful degradation, a core requirement for production-grade agentic systems operating in unreliable environments
View ProjectTraceLab - Medical Device Software Compliance Platform
December 1, 2025 – January 1, 2026
Built an AI-powered compliance platform for the regulated healthcare/life-sciences domain – orchestrating Google Gemini and a local MedGemma model to automatically extract and validate requirements against FDA 21 CFR Part 11 and ISO 13485 standards Designed an automated, agent-style pipeline that extracts requirements, generates test cases, executes them, and produces a traceability matrix – without manual intervention at any step, directly demonstrating end-to-end agentic workflow design in a regulated industry Designed an intelligent traceability matrix mapping generated test cases back to source code and compliance documents - significantly reducing manual QA overhead; deployed live at trace-lab.vercel.app
CodeGuardian – AI-Powered Institutional Memory System
August 1, 2025 – June 1, 2026
Built a production agentic AI system – implemented a Model Context Protocol (MCP) server exposing 9 autonomous tools (dependency analysis, compliance scanning, test generation) that AI agents like Claude Code and GitHub Copilot invoke independently to complete multi-step tasks without human intervention Engineered a RAG pipeline using NVIDIA NIM embeddings and a ChromaDB vector store - grounding agent responses in live, retrieved context to eliminate hallucinations, a core requirement for reliable agentic systems Designed the tool orchestration layer connecting multiple specialized tools behind a single agent-accessible interface - directly analogous to multi-agent workflow orchestration in enterprise systems Applied prompt engineering for engineering productivity – using Claude Code and GitHub Copilot to accelerate implementation of the RAG pipeline and MCP server while maintaining full architectural ownership and catching AI-generated code errors
View ProjectIntroduction to Databases with SQL
Harvard CS50
June 1, 2026 – Present
Introduction to AI & Machine Learning
Harvard CS50
June 1, 2026 – Present
Introduction to Programming with Python
Harvard CS50
June 1, 2026 – Present
Machine Learning I
Columbia
June 1, 2026 – Present
Data Science
Infosys
June 1, 2026 – Present
Natural Language Processing
Infosys
June 1, 2026 – Present
Cloud Computing
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from AI-powered institutional memory to medical device compliance and agricultural platforms, indicates a broad interest and ability to apply AI solutions across different domains. Their involvement in hackathons and publishing a conference paper suggests a proactive and collaborative attitude. The focus on agentic AI and full-stack development aligns well with the target role of an AI Engineer, particularly in an innovative environment.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through complex project implementations and an ownership-driven mindset. Their experience in team leadership and rapid prototyping suggests good operational fit for agile environments. The ability to work with AI-first development workflows indicates adaptability and a forward-thinking approach.