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AI Engineer with 4+ years in LLM Systems & Python Backend
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Assessing your cultural and operational fit
GenAI Engineer with 4+ years of experience building scalable backend systems, enterprise platforms, and production-grade AI workflows. Specialized in multi-tenant RAG architectures, LLM evaluation, and stateful agentic pipelines using LangGraph, pgvector, Model Context Protocol (MCP), FastAPI, and Celery.
University of Mumbai
B.E. · Information Technology
August 1, 2017 – June 30, 2020
Aditya Birla Group
AI Full Stack Engineer
March 1, 2025 – Present
Mumbai, Maharashtra, India
Turing
AI Full Stack Engineer
October 1, 2024 – January 1, 2025
India
upGrad
Full Stack Developer
September 1, 2023 – April 1, 2024
Bengaluru, Karnataka, India
Chesa
Full Stack Developer
July 1, 2021 – September 1, 2023
Bengaluru, Karnataka, India
Cultural Fit Analysis
The candidate has worked in diverse environments, from large enterprises (Aditya Birla Group) to startups (Turing, upGrad, Chesa), indicating adaptability. Their experience spans full-stack development to specialized AI engineering, showing a broad skill set and willingness to evolve. The projects highlight innovation (GenAI adoption, real-time collaboration) and a focus on measurable impact (accelerating content output, raising user retention), which aligns with a dynamic, results-driven culture. The breadth of technologies and problem domains suggests a curious and continuous learning mindset.
Soft Skills & Operational Fit
The candidate's resume demonstrates strong problem-solving skills through the detailed descriptions of complex system architectures (e.g., Rambo, document processing pipelines). Their experience in agile environments and leading technical roadmaps (OdinSculpt) suggests good operational fit and leadership potential. The focus on optimizing performance, reducing hallucinations, and integrating analytics indicates a results-oriented approach. The detailed descriptions of their work imply strong communication skills in a technical context.