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sanjay varghese stephen

Principal Engineer | Enterprise AI & Distributed Systems Architect | GenAI | RAG | LLMs | Cloud-Native Platforms | AWS | AI Agents | MS Applied Artificial Intelligence @ University of San Diego

Bengaluru

10+ years of work experience

McKinsey & Company
May 20251 yr 7 mosPresent

Bengaluru

·        Architected and delivered enterprise-grade AI solutions for automated analysis of Media Service Agreements (MSA) and Statements of Work (SOW), enabling compliance validation against standard contracting practices and generating detailed spend intelligence reports. ·        Reduced contract teardown and spend analysis turnaround time from multiple weeks to under 5 minutes through intelligent document processing, AI-driven workflow automation, and scalable cloud-native architectures. ·        Designed and implemented Retrieval-Augmented Generation (RAG)-based workflows leveraging Large Language Models (LLMs) for contextual document understanding, compliance analysis, semantic reasoning, and financial insight generation. ·        Architected an AI-powered conversational intelligence platform capable of dynamically orchestrating domain-specific APIs to deliver marketing analytics, campaign performance insights, benchmark analysis, and spend optimization recommendations based on enterprise client data. ·        Designed multi-agent orchestration frameworks using LangGraph and LangChain to enable scalable reasoning workflows, API execution, structured report generation, and enterprise AI automation. ·        Implemented vector database architectures for semantic search, contextual retrieval, and high-accuracy AI response generation across large-scale enterprise document repositories. ·        Partnered with global consultants, architects, and business stakeholders to define AI strategy, accelerate operational efficiency, and improve data-driven decision-making for enterprise clients. ·        Built and mentored high-performing engineering teams focused on scalable AI platform development, cloud-native modernization, and enterprise AI adoption initiatives. Tech Stack : Python, LLMs, RAG, LangChain, LangGraph, AI Agents, Vector Databases, AWS, Microservices, Semantic Search
Trellix
Feb 20241 yr 4 mosMay 2025

Bengaluru

·         Architected cloud-native database activity monitoring solutions for enterprise-scale cybersecurity platforms supporting secure monitoring across cloud-hosted database environments. ·         Designed and implemented high-performance multithreaded processing frameworks that improved database sensor efficiency by over 10x, significantly enhancing scalability and threat detection performance. ·         Led modernization initiatives for Java-based monitoring and vulnerability reporting platforms, driving improvements in platform maintainability, performance, and operational reliability. ·         Provided technical leadership to cross-functional engineering teams of 18+ engineers delivering enterprise-grade database security and threat monitoring solutions. ·         Drove engineering best practices, architecture governance, and scalable system design initiatives across distributed cybersecurity platforms. ·          Built and scaled engineering teams with diverse technical backgrounds while mentoring engineers in solution design, feature delivery, and customer issue resolution. ·         Collaborated with global architects and senior leadership teams to define platform delivery strategy, modernization roadmaps, and long-term security architecture initiatives.
Kinaxis
May 20221 yr 10 mosFeb 2024

Bengaluru

·    Architected and implemented high-performance forecasting algorithms for Demand AI platforms processing over 200,000 historical sales records per second across enterprise supply chain environments. ·    Designed scalable shipment forecast disaggregation and spreading algorithms to improve forecasting accuracy and supply chain planning efficiency. ·    Optimized large-scale algorithmic processing pipelines to support enterprise demand planning and predictive analytics initiatives. ·    Collaborated with global architects, product teams, and senior leadership to define roadmap strategies for AI-driven supply chain forecasting solutions. ·    Partnered with enterprise customers to resolve complex forecasting and algorithmic challenges across large-scale production environments. Tech Stack: C++, Windows, Microservices, XML
Nasdaq
Feb 20184 yrs 6 mosJul 2022

Bengaluru, Karnataka, India

·    Architected and delivered high-performance SaaS-based matching solutions for secondary financial markets capable of processing 25,000+ order transactions per second. ·    Designed and implemented low-latency gateway integrations including FIX, OUCH, and HURL protocols for seamless connectivity with universal matching engines. ·    Collaborated with global architecture teams to define scalable data models, distributed system designs, and platform integration strategies for financial trading systems. ·    Drove technology modernization initiatives through adoption of Agile engineering practices, scalable microservices architectures, and cloud-native deployment models. ·    Mentored and coached engineering teams in Bangalore while promoting engineering excellence, scalable architecture principles, and high-performance system design. Tech Stack: C++, Python, Distributed Systems, Microservices, PostgreSQL, AWS, Kubernetes, Docker
Jan 20162 yrs 2 mosFeb 2018

Bangalore

·    Architected and developed scalable REST API frameworks enabling enterprise storage migration from EqualLogic to next-generation Cyclone storage arrays. ·    Enhanced Linux Host Integration Toolkit compatibility across newer Linux platform releases, improving enterprise deployment stability and customer adoption. ·    Contributed to distributed systems modernization initiatives and promoted Agile engineering methodologies across cross-functional development teams. ·    Mentored early-career engineers and supported technical onboarding initiatives focused on scalable systems engineering and enterprise storage platforms. Tech Stack: C++, Python, Distributed Systems

sanjay’s AI Stack

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claude code
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cursor
cursor
gemini
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langgraph
langgraph
lovable
lovable

Education

Anna University Chennai

Bachelor's Degree, Computer Science

Anna University Chennai

20034 yrs2007
University of San Diego

Master's Degree, Applied Artificial Intelligence

University of San Diego

20262 yrs2028

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Headline

Principal Engineer | Enterprise AI & Distributed Systems Architect | GenAI | RAG | LLMs | Cloud-Native Platforms | AWS | AI Agents | MS Applied Artificial Intelligence @ University of San Diego

About

Principal Engineer and Enterprise AI Architect with 18+ years of experience building high-scale distributed systems, AI-powered platforms, and cloud-native enterprise solutions across consulting, cybersecurity, fintech, retail, telecom, and supply chain domains. Specialized in architecting enterprise-grade Generative AI platforms leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, LangChain, LangGraph, vector databases, and scalable orchestration frameworks. Proven track record delivering: AI-powered automation platforms reducing complex document analysis timelines from weeks to under 5 minutes Distributed financial systems processing 25,000+ transactions per second AI forecasting platforms processing 200,000+ historical records per second Experienced in leading global engineering teams, driving modernization initiatives, architecting scalable cloud-native systems, and partnering with business stakeholders to deliver enterprise-scale AI transformation. Core expertise includes: Generative AI | LLMs | RAG | LangChain | LangGraph | Distributed Systems | AWS | Kubernetes | Microservices | Cloud Architecture | AI Agents | Platform Engineering | Scalable Systems

Location

Bengaluru

AI stack

claude code

claude

cursor

gemini

langgraph

lovable

Work experience

Principal Software Engineer at McKinsey & Company, May 2025 - Present · 1 yr 7 mos, Bengaluru, · Architected and delivered enterprise-grade AI solutions for automated analysis of Media Service Agreements (MSA) and Statements of Work (SOW), enabling compliance validation against standard contracting practices and generating detailed spend intelligence reports. · Reduced contract teardown and spend analysis turnaround time from multiple weeks to under 5 minutes through intelligent document processing, AI-driven workflow automation, and scalable cloud-native architectures. · Designed and implemented Retrieval-Augmented Generation (RAG)-based workflows leveraging Large Language Models (LLMs) for contextual document understanding, compliance analysis, semantic reasoning, and financial insight generation. · Architected an AI-powered conversational intelligence platform capable of dynamically orchestrating domain-specific APIs to deliver marketing analytics, campaign performance insights, benchmark analysis, and spend optimization recommendations based on enterprise client data. · Designed multi-agent orchestration frameworks using LangGraph and LangChain to enable scalable reasoning workflows, API execution, structured report generation, and enterprise AI automation. · Implemented vector database architectures for semantic search, contextual retrieval, and high-accuracy AI response generation across large-scale enterprise document repositories. · Partnered with global consultants, architects, and business stakeholders to define AI strategy, accelerate operational efficiency, and improve data-driven decision-making for enterprise clients. · Built and mentored high-performing engineering teams focused on scalable AI platform development, cloud-native modernization, and enterprise AI adoption initiatives. Tech Stack : Python, LLMs, RAG, LangChain, LangGraph, AI Agents, Vector Databases, AWS, Microservices, Semantic Search

Staff Software Engineer at Trellix, Feb 2024 - May 2025 · 1 yr 4 mos, Bengaluru, · Architected cloud-native database activity monitoring solutions for enterprise-scale cybersecurity platforms supporting secure monitoring across cloud-hosted database environments. · Designed and implemented high-performance multithreaded processing frameworks that improved database sensor efficiency by over 10x, significantly enhancing scalability and threat detection performance. · Led modernization initiatives for Java-based monitoring and vulnerability reporting platforms, driving improvements in platform maintainability, performance, and operational reliability. · Provided technical leadership to cross-functional engineering teams of 18+ engineers delivering enterprise-grade database security and threat monitoring solutions. · Drove engineering best practices, architecture governance, and scalable system design initiatives across distributed cybersecurity platforms. · Built and scaled engineering teams with diverse technical backgrounds while mentoring engineers in solution design, feature delivery, and customer issue resolution. · Collaborated with global architects and senior leadership teams to define platform delivery strategy, modernization roadmaps, and long-term security architecture initiatives.

Senior Algorithm Developer at Kinaxis, May 2022 - Feb 2024 · 1 yr 10 mos, Bengaluru, · Architected and implemented high-performance forecasting algorithms for Demand AI platforms processing over 200,000 historical sales records per second across enterprise supply chain environments. · Designed scalable shipment forecast disaggregation and spreading algorithms to improve forecasting accuracy and supply chain planning efficiency. · Optimized large-scale algorithmic processing pipelines to support enterprise demand planning and predictive analytics initiatives. · Collaborated with global architects, product teams, and senior leadership to define roadmap strategies for AI-driven supply chain forecasting solutions. · Partnered with enterprise customers to resolve complex forecasting and algorithmic challenges across large-scale production environments. Tech Stack: C++, Windows, Microservices, XML

Lead engineer at Nasdaq, Feb 2018 - Jul 2022 · 4 yrs 6 mos, Bengaluru, Karnataka, India, · Architected and delivered high-performance SaaS-based matching solutions for secondary financial markets capable of processing 25,000+ order transactions per second. · Designed and implemented low-latency gateway integrations including FIX, OUCH, and HURL protocols for seamless connectivity with universal matching engines. · Collaborated with global architecture teams to define scalable data models, distributed system designs, and platform integration strategies for financial trading systems. · Drove technology modernization initiatives through adoption of Agile engineering practices, scalable microservices architectures, and cloud-native deployment models. · Mentored and coached engineering teams in Bangalore while promoting engineering excellence, scalable architecture principles, and high-performance system design. Tech Stack: C++, Python, Distributed Systems, Microservices, PostgreSQL, AWS, Kubernetes, Docker

Senior Engineer at DELLEMC, Jan 2016 - Feb 2018 · 2 yrs 2 mos, Bangalore, · Architected and developed scalable REST API frameworks enabling enterprise storage migration from EqualLogic to next-generation Cyclone storage arrays. · Enhanced Linux Host Integration Toolkit compatibility across newer Linux platform releases, improving enterprise deployment stability and customer adoption. · Contributed to distributed systems modernization initiatives and promoted Agile engineering methodologies across cross-functional development teams. · Mentored early-career engineers and supported technical onboarding initiatives focused on scalable systems engineering and enterprise storage platforms. Tech Stack: C++, Python, Distributed Systems

Education

Bachelor's Degree, Computer Science, Anna University Chennai

Master's Degree, Applied Artificial Intelligence, University of San Diego