AI Engineer with 2+ years in AI/ML & RAG pipeline development
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Results-driven AI Engineer with 1+ year of production experience architecting LLM-powered systems, Agentic AI workflows, and RAG pipelines. Proven delivery: 35% accuracy lift on ML models, 40% latency reduction on live APIs, and 90% manual-effort cut via LLM automation. Skilled across the full AI lifecycle – data engineering, fine-tuning LLMs, prompt engineering, vector database design (Qdrant/Pinecone), and containerised deployment (Docker, Kubernetes).
Parul University
Master of Computer Applications (MCA)
August 1, 2023 – June 1, 2025
SDAU
Bachelor of Science (Hons)
July 1, 2018 – June 1, 2022
Repidops
AI/ML Engineer (Entry Level)
January 1, 2026 – Present
Ahmedabad, Gujarat, India
Sopan Digital Solution
Full-Stack AI/ML Engineer
November 1, 2024 – January 1, 2026
Vadodara, Gujarat, India
Techinfoplace Softwares Pvt. Ltd.
Front-End Developer
March 1, 2023 – September 1, 2023
Vadodara, Gujarat, India
Stock Trend Predictor
June 8, 2026 – Present
Developed a multi-layer LSTM forecasting model with live cron-triggered retraining and sliding-window updates. demo: stock-price-prediction-1-x6lw.onrender.com
Insurance Aggregator Platform
June 8, 2026 – Present
Developed a full-stack insurance comparison platform aggregating real-time quotes from 10+ provider APIs, normalising data for standardised display - serving 1K+ monthly users. Live: allautoinsurancequote.com
Blog Automation Agent
June 8, 2026 – Present
Built an automated workflow to generate SEO-ready blog articles using LLMs, format them in HTML/CSS, and publish via Gmail.
AI Crop Intelligence Platform
June 8, 2026 – Present
Designed an Agentic AI system using LangGraph multi-agent orchestration for real-time crop disease detection, yield forecasting, and personalized advisory. Constructed end-to-end RAG pipeline: PDF/web ingestion → text chunking → sentence-transformer embeddings → Qdrant vector store → LangChain retrieval chain → Gemini-powered response synthesis, achieving 92% answer relevance. Integrated a continuous learning loop - LangGraph agent auto-fetches new agri-research weekly, re-embeds and upserts into Qdrant, ensuring zero manual knowledge-base maintenance. Containerised all microservices with Docker and orchestrated on Kubernetes (HPA-enabled), delivering 99.5% uptime and auto-scaling during peak harvest-season load.
Fake SMS & Link Detector
June 8, 2026 – Present
Built an NLP phishing-detection classifier achieving 92% precision on SMS and malicious-link identification, deployed as a Flask API with an interpretability dashboard for flagged samples.
NCC Level B & C
Unknown
June 1, 2026 – Present
Networking & Protocols
NPTEL
June 1, 2026 – Present
Machine Learning
DeepLearning.ai
June 1, 2026 – Present
Front-End Developer
BIT
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio shows a diverse range of applications, from agriculture and finance to security and content generation, indicating adaptability and a broad interest in applying AI to different domains. The focus on building end-to-end solutions and integrating continuous learning loops aligns with a proactive and innovative culture. The experience with both individual projects and team roles (though limited in detail for team collaboration) suggests a capacity to work in varied environments. However, the experience level is relatively junior for a senior role, which might require more mentorship.
Soft Skills & Operational Fit
The candidate's project descriptions highlight a results-driven approach, focusing on metrics like accuracy uplift, latency reduction, and uptime. This indicates a strong operational mindset and a focus on delivering tangible business value. The continuous learning loop implemented in the 'AI Crop Intelligence Platform' project suggests proactivity and an ability to design self-maintaining systems. The experience in front-end development also implies an understanding of user experience, which is valuable for deploying AI solutions.