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Principal AI Architect | Production LLM Systems, RAG & Agentic Workflows | Automotive & Fintech
With 15 years of experience spanning Solution Architecture, Full Stack Engineering, and AI/LLM Systems, I design and deliver enterprise-scale platforms that bridge business strategy with technical execution. I have led teams of 20+ engineers and architected solutions across Automotive, FinTech, eCommerce, Banking, Healthcare, Telecom, and OTT domains — from system design through global production rollout. Currently at Stellantis, I am leading the architecture of the Global Digital Store Platform powering subscription services and ePayments for connected vehicles across Jeep, Fiat, Alfa Romeo, Opel, Citroën, Peugeot, and DS Automobiles. My work covers OAuth2 QR-based in-vehicle authentication, multi-brand API design using OpenAPI 3.0, serverless backend development with AWS Lambda, and full CI/CD automation via CodePipeline and Terraform. I collaborate with engineering teams across Bangalore, Turin, and Paris to define standards, conduct architecture reviews, and drive consistent delivery. Beyond my primary role, I build AI products end-to-end. I designed MeetMind, a production-grade real-time meeting assistant combining RAG pipelines, live speech-to-text using Faster-Whisper, and autonomous agentic workflows — achieving 90%+ LLM cost reduction through multi-model orchestration. I also built EnterpriseGPT, a fully air-gapped on-premise AI assistant with a fine-tuned Gemma 3 model using QLoRA, delivering a ChatGPT-like experience with 100% data sovereignty and zero external API dependency. Key achievements include growing NMMS platform revenue from $13M to $46.3M within 18 months, leading a microservices migration at Marvell Technology, and driving Micro Frontend Architecture at Tesco that eliminated cross-team deployment dependencies across four European markets. My core expertise spans Solution Architecture, Microservices, Event-Driven and API-First desig
Cathedral College, Bangalore
PRE-DEGREE
N/A – Present
Cathedral High School, Bangalore
ICSE
N/A – Present
PESIT, Bangalore
Bachelor of Engineering (B.E.), Information Science
N/A – Present
Marvell Technology
Solutions Architect
September 1, 2020 – Present
On-site
Marvell Technology
Web Technologies Senior Professional
September 1, 2019 – Present
On-site
Tesco
SDE2
July 1, 2019 – August 1, 2020
Bengaluru, Karnataka, India
Envestnet | Yodlee India
Member Of Technical Staff
June 1, 2017 – July 1, 2019
bangalore
Morgan Stanley
Senior Associate
February 1, 2016 – June 1, 2017
Accenture
Software Engineer
September 1, 2013 – February 1, 2016
Bangalore
REVtech Solutions India Private Limited
Software Engineer
February 1, 2013 – September 1, 2013
Bangalore
GlowTouch Technologies
Software Engineer
March 1, 2011 – January 1, 2013
Mangaluru, Karnataka, India
Cultural Fit Analysis
The candidate has a long and varied career primarily focused on front-end and full-stack web development, with roles in financial services, retail, and technology companies. The target role is 'ML Engineer', which represents a significant pivot from their documented experience. While the candidate has a Bachelor of Engineering in Information Science, there is no explicit mention of machine learning, data science, or related projects/skills in their work history. This lack of direct alignment with the target role suggests a low cultural fit for an ML Engineer position without further evidence of relevant skills or interest.
Soft Skills & Operational Fit
The candidate's resume indicates experience in roles like Solutions Architect and Senior Associate, suggesting leadership and problem-solving skills. However, without psychometric test results or interview data, a definitive assessment of soft skills and operational fit is not possible.