Systems Thinker. AI Platform Architect. Fractional CTO.

CTO-level engineering leader with 30+ years of continuity across platform engineering, distributed systems, SaaS modernization, and production-grade AI-native product architecture. I bridge the critical gap between executive product vision and hands-on technical execution.

What keeps me in this work after three decades is the same thing that got me into it: the moment a system that used to fight you starts working with you instead.

Available for fractional mandates · up to 20 hrs/week · 15 days’ notice

Download Short CV ↓ Download Detailed CV ↓

Credentials MIT Exec Ed Johns Hopkins BITS Pilani IIT Madras

System Topology / Live Context

Career Timeline

1994

Started as a programmer — GM/GMAC, Remedy

2003

Co-founder & Technical Director, TechnoTryst

2014

Director of Technology, media & streaming

2022

CTO — 1,100+ engineers, $20M+ portfolio

2026

Fractional CTO & independent builder

Current Focus Matrix

Active Pillar

AI Systems & Agentic Workflows

Architecting asynchronous, event-driven microservices designed for intensive, heavy-I/O model inference pipelines.

Active Pillar

PropTech Intelligence Platforms

Engineering scalable spatial and data platforms for real estate, utilizing modern stacks to accelerate property search and asset valuation algorithms.

Active Pillar

AI-Driven Decision Engines

Implementing hybrid machine learning models and predictive analysis layers to generate automated workflows in regulated domains.

Active Pillar

Fractional Leadership

Providing fractional CTO advisory and zero-to-one product engineering governance without the overhead of a full-time executive.

Selected Architectural Case Studies

AI Risk Assessment Engine (FinTech)

Context: Enterprise SaaS CRM + payment platform modernization for the US credit card sector.
Architecture: Monolithic to event-driven microservices migration. Developed a hybrid Python and ML-driven transaction monitoring model.
Outcome: Lowered false-positive alert rates, drastically increased deployment speed, and slashed infrastructure failures by 40%.

Python ML Event-Driven Microservices SaaS CRM

Intelligent Document Processing Pipeline (Healthcare Tech)

Context: Global capability center transformation managing high-volume data assets.
Architecture: Secure Retrieval-Augmented Generation (RAG) platform leveraging LangChain, vector storage, and Python asynchronous microservices.
Outcome: Reclaimed thousands of manual review hours by shifting chart analysis into an automated, highly accurate extraction workflow.

LangChain RAG Vector Storage Python Async

Enterprise Digital Commerce Engine (SaaS Scaling)

Context: Global delivery portfolio tracking a $20M+ P&L and 1,100+ technical assets.
Architecture: Multi-tenant COTS platforms unified with lightweight, distributed web accelerators.
Outcome: Standardized automated CI/CD practices and introduced AI-assisted developer frameworks to optimize release engineering.

Multi-Tenant SaaS CI/CD COTS AI-Assisted Dev Frameworks

Core Mindset & Technical DNA

AI Engineering

Python
LangChain
OpenAI APIs
MLOps
Text embeddings
Custom extraction workflows

Platform Foundations

Multi-tenant SaaS
AWS/GCP architecture
Docker
Kubernetes
CI/CD
Test-Driven Development (TDD)

The Differentiator: Continuity across technology eras. From early web-tier architectures to modern enterprise AI, my value lies in selecting tech stacks based on true economic outcomes, not market hype.