Generative AI Engineer with 2+ years in GenAI systems, RAG pipelines, and FastAPI backends.
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Generative Al Engineer with production experience building GenAl systems, multi-agent orchestration platforms, RAG pipelines, and scalable FastAPI backends on AWS. Delivered systems handling 500+ daily queries at sub-200 ms p95 latency, reduced retrieval latency by 35%, and automated 15+ hrs/week of manual work. Deep hands-on expertise in LangChain, LangGraph, CrewAl, OpenAl API, Pinecone, FastAPI, Docker, and Python. Recognised with Rockstar of the Month and Pinnacle Award at Zepto. CGPA 9.6/10.
Bapurao Deshmukh College of Engineering, Wardha
B.Tech · Computer Science & Engineering
August 1, 2018 – June 30, 2022
Zepto
Generative AI Engineer
June 1, 2024 – Present
Mumbai, Maharashtra, India
Multimodal RAG Knowledge Assistant
June 23, 2026 – Present
• Developed multimodal RAG system: unified ingestion and retrieval pipeline for PDFs, images, voice, and video (5+ formats) at sub-300 ms end-to-end query latency. • Engineered hybrid retrieval: OCR + Whisper STT + dense embeddings + re-ranking + metadata filtering for high-precision document QA. • Scaled async FastAPI backend with chunking optimisation and Pinecone namespace partitioning for multi-tenant knowledge base management.
View ProjectReal-Time AI Interview Copilot
June 23, 2026 – Present
• Built real-time AI assistant: WebSockets + streaming inference with sub-500 ms end-to-end latency, live Whisper speech-to-text, and streamed LLM output on React frontend. • Personalised contextual answer generation dynamically adapted to candidate's resume and target JD.
LLM Fine-Tuning & Evaluation Pipeline
June 23, 2026 – Present
• Fine-tuned Mistral-7B using QLoRA (4-bit quantisation) on a single GPU — achieved 18% improvement on task-specific benchmarks vs base model. • Built MLflow experiment tracking pipeline: hyperparameter logging, checkpoint management, model registry, and automated RAGAS eval (faithfulness, relevancy, context recall).
View ProjectAutonomous AI Employee System
June 23, 2026 – Present
• Architected multi-agent AI system: orchestrated 5+ autonomous agents for email automation, scheduling, and reporting using LangGraph + CrewAI — saving ~15 hrs/week of manual work. • Built persistent memory & integrations: implemented long-term episodic memory via Pinecone and connected Gmail, Slack, and Google Calendar via OAuth 2.0 and webhook-driven event handling. • Ensured reliability: added RAGAS evaluation suite with regression tests and failure-injection cases for non-deterministic agent testing.
View ProjectAWS Certified Cloud Practitioner
Amazon Web Services
June 1, 2026 – Present
Spring Boot & Microservices
Udemy
June 1, 2026 – Present
Generative AI Systems - LLMs, RAG & Prompt Engineering
Coursera / DeepLearning.AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for a Generative AI Engineer role through diverse projects focusing on cutting-edge AI applications (multimodal RAG, real-time AI copilot, autonomous agents, LLM fine-tuning). Their experience at Zepto as a Generative AI Engineer directly aligns with the target role, showcasing practical application of advanced AI concepts in a production environment. The breadth of skills across AI/GenAI, ML/DL, Backend, and Cloud/DevOps, combined with open-source contributions, indicates a continuous learning mindset and a passion for the field.
Soft Skills & Operational Fit
The candidate's resume highlights significant achievements and leadership roles, such as 'Rockstar of the Month' and 'Pinnacle Award' at Zepto, indicating strong work ethic, impact-driven approach, and ability to deliver high-quality results. Leadership experience as 'Technical Head' and open-source contributions suggest initiative, collaboration, and a proactive learning attitude. The focus on performance metrics (latency, automation percentage) in project descriptions indicates a results-oriented mindset.