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AI Engineer with less than a year in Computer Vision & ML APIs
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Shriharee Panchal is an enthusiastic B.Tech AI & DS student (expected 2026) with 11 months of production experience in agentic AI, computer vision, and ML APIs. He has successfully built LangGraph multi-agent RAG pipelines with adversarial guardrails and fine-tuned Falcon-7B models to 4-bit. Shriharee is available immediately and open to relocation, demonstrating a strong foundation in AI/ML and a proactive approach to real-world applications.
Maharashtra Institute of Technology
B.Tech · Artificial Intelligence & Data Science
September 1, 2023 – May 1, 2026
Mowito Automation Private Limited
Computer Vision Intern
January 1, 2026 – May 1, 2026
Bengaluru, Karnataka, India
CVFrameIQ
Computer Vision Intern
September 1, 2025 – December 1, 2025
India
Outrix
Machine Learning Intern
August 1, 2025 – September 1, 2025
India
LLM Financial Assistant
June 24, 2026 – Present
Streamed live financial news through a Bytewax pipeline into Qdrant, embedding 10K+ articles for grounded RAG retrieval. QLoRA-quantized Falcon-7B to 4-bit, cutting fine-tuning VRAM 65% while holding domain Q&A accuracy within margin of full fine-tune. Served the pipeline via FastAPI + Streamlit on Render, chaining LangChain retrieval with conversational memory for multi-turn financial queries.
View ProjectAgentic RAG Chatbot
June 24, 2026 – Present
Built a LangGraph agent with 4-step dynamic tool routing, benchmarked against naive single-pass retrieval to cut irrelevant results 35% on a 20K-document test set. Engineered a 6-format ingestion pipeline with adaptive chunking into ChromaDB, holding query latency under 2 seconds at corpus scale. Layered 3 LLM guardrails (PII redaction, injection detection, confidence gating) across 4 swappable providers, validated against a 50-prompt adversarial test set to flag 40% more unsafe outputs pre-response.
View Project200+ DSA problems on LeetCode and GeeksforGeeks
Unknown
June 1, 2026 – Present
Diploma Rank 2
Unknown
June 1, 2026 – Present
SIH 2025 Internal Hackathon Winner
Unknown
January 1, 2025 – Present
Hackground India 2025, GO-FR Hackathon Participant
Unknown
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's profile shows a strong alignment with an AI Engineer role, demonstrating hands-on experience across various facets of AI, including LLMs, computer vision, and general machine learning. The participation in hackathons and extensive DSA practice indicates a proactive and continuous learning mindset, which is a good cultural fit for dynamic tech environments. The breadth of technologies used in personal projects suggests curiosity and self-driven learning.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong focus on measurable outcomes and performance improvements, suggesting a results-oriented approach. The experience in setting up evaluation harnesses and CI/CD pipelines points to an understanding of operational best practices and a methodical approach to development. The diverse project work also implies adaptability and a willingness to tackle complex challenges.