AI Solutions Architect specializing in enterprise software, cloud platforms, intelligent automation, recruiting technology, predictive analytics, and modern SaaS products.
Enterprise AI Platforms Built
ML Systems Designed
Cloud Deployments
Business Workflows Automated
Specializing in
I started where most engineers do shipping features. But I kept being drawn to the harder questions behind them: How does this scale to a thousand tenants? How do we keep every customer's data provably isolated? How do we make an AI system that a recruiter, a CTO, and an auditor all trust?
Over time I moved from writing features to owning architecture designing multi-tenant SaaS platforms, document AI pipelines, and cloud-native systems on Azure. Today I work as an AI Solutions Architect, building AI-powered enterprise software end-to-end: the data, the models, the platform, the security, and the product.
I enjoy difficult business problems because that's where architecture actually matters. The satisfying part isn't the model it's turning a messy, real-world workflow into a system that quietly does its job at scale.
Great architecture is invisible. I begin with the outcome a business needs and work backward to the simplest system that delivers it reliably.
Multi-tenancy, security and observability aren't features you bolt on later — they're the foundation every enterprise product is built on.
From data pipelines and model serving to the UI and deployment, I own the whole product surface so the pieces actually fit together.
For AI that people must trust, the answer isn't enough — the reasoning is the product. I build systems that show their work.
Each project below is a complete case study — architecture, security, scale, results and lessons. Not demos; products.
The reference architecture behind the products in this portfolio — cloud-native, multi-tenant, observable and secure by default.
Fast, accessible interfaces rendered on the edge.
Typed, versioned services with tenant-aware routing.
Retrieval, document AI and hybrid local/hosted inference.
Relational + vector storage tuned for search at scale.
Containerized, observable, zero-downtime delivery.
Isolation, identity and auditability by default.
No progress bars — just the capability areas I design and ship across, from architecture down to the database.
Designing systems that scale from first customer to org-wide rollout.
High-throughput services and data pipelines.
Fast, accessible, product-grade interfaces.
Applied AI, ML modeling, retrieval and document intelligence.
Cloud-native data platforms built for reliability.
Ship continuously, observe everything.
Enterprise-grade trust and compliance.
Modeling and moving data for scale, analytics and search.
Education, career, projects and milestones — filter to trace a single thread through the story.
Raghu Institute of Technology
Graduated May 2020 — the engineering foundation (algorithms, data structures, ML) behind everything that came after.
B.Tech Capstone
Regression + gradient-descent model predicting agricultural yield — the award-winning capstone project.
Crisp Croft
Built cloud ETL pipelines on Azure and Snowflake and ML forecasting systems for crop yield and demand prediction.
Amazon Development Center
Developed predictive ML models for driver safety over 500,000+ events, reaching 95% prediction accuracy.
Enterprise / ERP
Delivered eRecruit enhancements with PeopleCode and SQL — recruiting workflow automation and applicant screening.
Predictive Analytics
K-Means clustering and Random Forest classification to profile driver risk, trigger alerts and drive coaching.
DePaul University
Owned analytics across 15+ buildings and 1,000+ assets, automating reporting for 40% faster turnaround.
DePaul University
Graduated with a Master's in Business Analytics — the bridge from data analysis to AI platform architecture.
HR Technology
Document-AI for PDF/DOCX parsing, entity extraction with confidence scoring and resume-to-job semantic matching.
Machine Learning
Real-time /predict ensemble pipeline, CALLS/PUTS decision engine and EDGAR XBRL fundamental analysis.
Financial Analytics
Profitability, leverage, liquidity and efficiency ratio analysis framed as an investment thesis.
VR IT Resources · Sterling, VA
Architect and build enterprise AI and data platforms end-to-end — SQL analytics, AI recruiting and conversational AI.
Founding Architect
Architected a multi-tenant AI recruiting platform: semantic matching, vector embeddings and ML candidate ranking.
Applied AI
NLP-based service discovery, knowledge retrieval and document lookup on Azure to reduce call-center load.
SaaS Platform
Outbound sales platform with lead management, AI outreach drafts and a human approval queue on a CRM-ready architecture.
Enterprise AI
Building enterprise AI platforms end-to-end — from data pipelines and local LLM workflows to secure, multi-tenant SaaS.
Roles where I owned architecture and outcomes — with the business impact and technologies behind each.
VR IT Resources · Sterling, VA
Architect and build enterprise AI and data platforms end-to-end — from large-scale SQL analytics pipelines to AI recruiting intelligence and conversational assistants.
DePaul University · Chicago, IL
Owned analytics and reporting across a large facilities portfolio, automating pipelines and enabling faster, data-driven decisions.
Amazon Development Center · Hyderabad, India
Built predictive ML models and analytics for driver safety and operational risk at scale.
Crisp Croft · Hyderabad, India
Built cloud data platforms and ML forecasting systems on Azure and Snowflake.
A Master's in Business Analytics plus continuous, self-directed depth across AI, cloud and data engineering.
DePaul University · 2024
Applied Specialization · 2024
Focus Area · 2023
Focus Area · 2022
Focus Area · 2025
Focus Area · 2022
Honors & Leadership
Dean's Award for Scholastic Excellence
DePaul University
2024
Case Competition Winner
Capstone Project · DePaul University
2024
Senator, International Students
Student Government Association · DePaul University
2024
Placeholder references — replace with real quotes from the engineering and talent leaders you've worked with.
“Sai doesn't just build features — he architects the whole product. He sees the business problem, the system, and the customer at once.”
VP of Engineering
Enterprise SaaS
“The recruiting platform he designed reduced our screening time dramatically. It felt like working with a founding CTO, not a contractor.”
Head of Talent
Recruiting Technology
“Rare combination of deep AI knowledge and enterprise discipline — security, tenancy and scale were considered from day one.”
Chief Technology Officer
HR Technology
Long-form articles on architecture, applied AI and building enterprise platforms. Early drafts — full pieces on the way.
Have a hard business problem, an AI platform to architect, or a role to fill? I read every message.
