AI Engineer with 1+ years in LLM & RAG Systems and Agentic AI workflows.
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AI Engineer with hands-on experience building and deploying production-ready LLM systems, RAG pipelines, and agentic AI workflows. Proven track record in end-to-end AI solution design - from identifying high-impact use cases and conducting proofs-of-concept, to piloting and scaling enterprise-grade products. Skilled in prompt engineering, model evaluation, multi-agent orchestration, and cloud deployment. Strong stakeholder communicator with experience gathering cross-functional requirements.
(MCIT) Ministry of Communications and Information Technology
Diploma (9-Month) · AI&ML
August 1, 2024 – June 30, 2025
MET Academy for Technology and Commerce
Bachelor of Computer Science
August 1, 2020 – June 30, 2024
G2i
AI Software Engineer
January 1, 2025 – January 1, 2026
India
Seer - Agentic AI Platform
June 1, 2026 – Present
• Designed and deployed a multi-agent agentic system automating end-to-end hardware design: market analysis → specification generation → CAD/PCB outputs; mirrors enterprise AI road-map delivery. • Orchestrated sequential agent handoffs with error recovery and output validation on cloud infrastructure, achieving a production-ready, scalable async architecture. • Built multi-step LLM prompt pipelines with structured engineering outputs; iteratively refined prompts and agentic logic based on stakeholder feedback. • Gathered requirements from project lead, assessed model outputs, and delivered phased improvements aligned to project KPIs.
View ProjectImmune Bot - RAG Chatbot
June 1, 2026 – Present
• Built a full RAG pipeline (PDF parsing → semantic chunking → embeddings → ChromaDB vector store) optimized for factual accuracy and hallucination reduction in domain-specific medical Q&A. • Applied hybrid retrieval strategies and prompt engineering to improve response reliability; deployed as a live 24/7 service on Hugging Face Spaces. • Defined and tracked evaluation metrics (accuracy, hallucination rate) to drive continuous model optimization.
View ProjectRecruiters RAG System
June 1, 2026 – Present
• Designed an end-to-end AI workflow: PDF parsing → structured extraction → embeddings → semantic search, significantly reducing manual screening effort. • Deployed on Gradio for interactive demo and testing; architected for scalable candidate discovery at enterprise scale.
View ProjectTeachFlow - AI Course Generator
June 1, 2026 – Present
• Built an end-to-end pipeline converting raw PDFs into structured courses using OCR, semantic chunking, and multi-stage LLM workflows with iterative refinement loops. • Exposed pipeline via Flask REST APIs for external access; designed for integration with enterprise content management workflows.
View ProjectWanderWise - AI Travel Planner
June 1, 2026 – Present
• Designed multi-step LLM workflow: user input → processing → structured itinerary generation with consistent, validated outputs. • Developed production-ready Flask backend APIs handling real-time requests with end-to-end user interaction.
View ProjectObesity Classification
June 1, 2026 – Present
• Built classification models using Scikit-learn on behavioral and physical datasets; performed feature engineering and model optimization to improve predictive accuracy. • Applied applied ML techniques (data preprocessing, cross-validation, hyperparameter tuning) — demonstrating hands-on experience with the ML Python stack (Pandas, NumPy, Scikit-learn).
View ProjectUnderstanding Artificial Intelligence
DataCamp
June 1, 2026 – Present
RPA Using UIPATH
MaharaTech
June 1, 2026 – Present
Mastering Object-Oriented Programming (OOP) using C++
MaharaTech
June 1, 2026 – Present
Foundation of GIT
DataCamp
June 1, 2026 – Present
Data Preparation
DataCamp
June 1, 2026 – Present
Cloud Computing & AWS Cloud Technology and Services Concepts
DataCamp
June 1, 2026 – Present
The Ultimate React Course: React, Next.js, Redux
Udemy
June 1, 2026 – Present
Linux Essentials
MaharaTech
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from agentic AI platforms to RAG chatbots and AI course generators, indicates a broad interest and adaptability in applying AI solutions. Their experience in a remote role at G2i suggests comfort with distributed teams. The academic background and continuous learning through certifications demonstrate a proactive approach to skill development, which aligns well with a culture of innovation and growth. The focus on enterprise-grade solutions and stakeholder feedback in projects also points to a strong business-oriented cultural fit.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills in stakeholder engagement, requirements gathering, and cross-functional coordination, which are crucial for an AI Engineer role. Their experience in leading A/B testing cycles and defining success metrics indicates an operational mindset focused on measurable outcomes. The ability to translate business needs into technical designs is a significant asset for project delivery.