I
Enterprise Scalability
Designing robust, highly-available cloud infrastructures capable of processing massive data throughput — without friction or failure.
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Available for select engagements — 2026
ARCHITECTING
Intelligence.
SCALING
Reality.
ARCHITECTING
Intelligence.
SCALING
Reality.
AI & Cloud Architect — Founder
I engineer scalable data platforms and distributed systems — bridging the gap between robust enterprise infrastructure and state-of-the-art agentic workflows.
Hi, I'm Soumya!
00
The Architect
ORCHESTRATING Intelligence
SYS.SYNC [OK]
AXIS: 0.124
NET: ACTIVE
ORBITAL.LOCK
SYSTEM_TELEMETRY
SYS_STATUS: ONLINE
SERVER_LOAD: 12.4%
NET_LATENCY: 21ms
NODE_COORDINATES
COORD_X: 0.0000
COORD_Y: 0.0000
ACTIVE_NODES: 154 / 200
MODULE_02 // CLOUD & DATA PLATFORMS
ENGINEERING Resilient PLATFORMS
Architecting highly-available distributed systems capable of handling 10M+ daily requests with decoupled, self-healing infrastructures.
WARP NETWORK GRID
INFRASTRUCTURE_DECOUPLED
AURORA_SERVERLESS
AMAZON_KINESIS
AWS_LAMBDA
AWS_BEDROCK
AWS_ECS
AWS_S3
NODE_LOGS
[INFO] Pipeline connected to Kinesis...
[INFO] Data buffer allocated successfully...
01
Philosophy
Engineering at the intersection
of scale and innovation.
The most complex business challenges aren't solved by writing more code; they are solved by designing better systems.
My approach merges the uncompromising reliability of enterprise cloud architecture with the velocity of modern artificial intelligence. Whether it is orchestrating autonomous, multi-agent AI systems or designing resilient backend infrastructures — my focus is on building platforms that don't just function.
They think. They adapt. They scale — seamlessly, from day one.
Soumya Swaraj
02
The Three Pillars
What I build.
How I think.
II
Applied AI & Agentic Workflows
Moving beyond basic LLM wrappers to engineer intelligent, multi-agent ecosystems that automate deep research and complex, multi-step problem-solving.
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III
Founder's Execution
Approaching engineering through the lens of a founder. Every architectural decision driven by product-market fit, user growth, and actionable business metrics.
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0M+
Daily requests routed
0M+
Compute hours saved
0K
Revenue in 60 days
0×
AWS certifications
03
Selected Work
How I engineer
solutions.
01
Evergrow
01 · Flagship Innovation · 2025 — Present
Evergrow
The AI Content OS
A comprehensive, Done-For-You intelligence service engineered for the new era of Search and Generative AI visibility. Evergrow bridges the gap between raw AI output and rigorous, authoritative brand building.
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Legacy Brands
Modernizing digital footprints to excel in AI-driven search paradigms and recapture market visibility.
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Startups
Accelerating domain authority — so you become the default, trusted brand actively recommended by Google, ChatGPT, and emerging LLMs.
Under the Hood — Multi-agent ecosystem with adversarial AI personas automating academic-grade research. Every piece deployed is rigorously verified, highly scalable, and structurally optimized for the future of search.
Impact — $200K revenue in 60 days for B2B SaaS. 7× organic traffic for tourism agencies in 100 days.
01
02
High-Availability
02 · Enterprise Infrastructure · JPMorgan Chase · 2019 — 2024
High-Availability
Infrastructure
Innovation requires a foundation of absolute reliability. As a Software Engineer, I spearheaded the architectural redesign of legacy data platforms — migrating thousands of accounting, settlement, regulatory and risk-management reports off legacy data platforms that were based on low latency but cost intensive RAM cluster object storage (some reaching TBs) for real time trading onto a cost effective and highly available cloud-native data platform.
The stack: Aurora Serverless, Kinesis, Firehose, Lambda, S3, SNS, Athena & others — designed as a decoupled replica of the legacy real-time system, offloading every workload that didn't need microsecond latency.
Scale — Seamlessly processing and routing 10,000,000+ daily requests with zero-downtime reliability in a high-stakes financial environment handling billions of dollars in daily transactions.
My work — Data Streaming Pipeline Design, Data Migration, Consumer SDK Development & Implementation, Anomaly detection, self-healing pipelines, platform optimization and migration tooling — contributing to $1M+ in annual savings in compute costs and operational efficiency.
See the metrics ↗02
03
Early LLM Agents
03 · Agentic LLMs · 2022 — Present
Early Enterprise
LLM Agents
One of the earliest enterprise adopters of agentic LLMs inside a tier-1 financial institution. Engineered LLM-powered monitoring agents with self-healing capabilities for financial reporting workflows — autonomously detecting, diagnosing, and resolving data anomalies before they reached downstream consumers.
Beyond monitoring, deployed specialized agents using RAG + few-shot prompting. Built On-Demand Natural Language → SQL engines that compressed 10 days of analyst work into exactly 10 minutes.
Scale — Distributed data platforms processing hundreds of millions of trade requests per day.
See architecture ↗03
04
Automation
04 · Automation · JPMorgan Chase
Automation
at scale
Optimized 400+ batch feeds handling millions of transactions daily across various business verticals (Fixed Income Finance, Commodities Finance, Derivatives, Regulatory Technology & more), saving 1.5M+ compute hours. Automated self-correction mechanics eliminating 80% of daily production issue tickets.
Principle — Efficiency is non-negotiable for enterprise workloads.
Learn more ↗04
05
Expertise
05 · Technical Authority
Infrastructure &
AI Expertise
6× AWS Certified — across architecture, networking, ML and development.
05
04
Track Record of Growth
Built things.
People showed up.
Before the enterprise chapters — a consistent history of shipping products that acquired real users, from bootstrap communities to organic-traffic platforms.
A Movie Recommendation Site
0M
Organic hits
Scaled a community-driven movie recommendation platform like IMDB but better, from zero to 15M organic hits — mastering search intent, content structure, and organic user acquisition through word of mouth. It was spread across over 20 colleges in India.
Early masterySearch intentContent systems
A Gaming Social Network
0K
Active members
Bootstrapped and grew a niche gaming social network for a couple of RPG games that I used to play earlier to 15,000 active users — in high school, after a 10-day PHP coding marathon. Early proof of product-market fit and community engagement. It collapsed under its own load. The lesson stuck.
First projectCommunityPMF
Appendix A — Also Built
Index of shipped work
Communities, internal platforms & micro-projects — an underappreciated compounding record.
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01
2020
COVID-19 Tracker
Pandemic Response 800K+ usersShipped during the pandemic — live case counts, regional breakdowns and trusted public-health guidance.
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02
2019
University Counseling System
30K studentsOn-site management system — cut processing time by 70%.
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03
2020
CMS for Virginia Tech & TIET
2 universitiesRobust content platforms. Web + mobile lead at the Google Developer Club.
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04
2019 — 21
Campus Ticketing & Apps
10K+ usersGo-to engineer for campus societies — systems handling tens of thousands of users.
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05
2014
Mobile Game Guide App
30K gamersStructured tools, walkthroughs and community Q&A.
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06
2015
White-Labeled Free Hosting
~100 sitesProvisioning service — before I knew the word "multi-tenant".
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07
2020
College Blogging Community
50K readsCo-built — 20K social reach. My first publishing platform.
05
The Backstory
Origin story.
Scalability limits everything.
2010
A Small Town, a Slow Modem
Growing up in Dhanbad — a 25 Mbps modem and an audacious dream. Fuelled by the desire to communicate across the globe, I coded my first social network from scratch.
2014 — 2015
The RPG Gaming Era
After a 10-day PHP coding marathon, I launched my clan based gaming social network that hit 15,000 members. The site collapsed under its own weight on shared hosting. That failure taught me a lesson I've used every day since: scalability limits everything.
2018 — 2020
Student. Builder. Lead.
Built a movie recommendation site to 15M organic hits. Shipped a counseling system used by 30K university students. Built CMSes for Virginia Tech and TIET. Ran web & mobile for the Google Developer Club. Became the campus's go-to engineer for anything that had to scale.
2022 — 2024
Enterprise — JPMorgan Chase
Re-architected legacy data platform into a cloud-native platform on Aurora Serverless, Kinesis, Firehose, S3, Lambda, SNS and others. Routed 10M+ daily requests. Built some of the earliest enterprise-grade LLM monitoring agents with self-healing capabilities. Contributed to $1M+ in annual savings.
2025 — Now
Founder — Evergrow
Building the AI Content OS — a multi-agent system with adversarial personas producing rigorously-researched, authoritative content for the age of generative search. Platforms that don't just scale — they actively drive revenue.
06
The Human Element
Beyond the
architecture.
Building scalable systems requires intense focus — but the best ideas often happen away from the screen.
When I'm not architecting AI ecosystems or optimizing cloud infrastructure, I'm usually resetting my competitive drive on the badminton court or diving into a good fiction novel. I prefer "chill" travel — finding quiet hill stations or beaches over high-intensity trekking — and I am perpetually on the hunt for the perfect cup of Adrak Chai.
Badminton
Fiction
Chill Travel
Adrak Chai
