Users first, stack second.
Start from the experience, then pick the simplest tech that delivers it.
Senior Full-Stack Engineer · Workday
I design, build and operate software end to end — web, mobile, cloud and applied AI — for teams that need it to work at scale.
Built with teams at






About
Hi, I'm Logesh — I build things that live on the internet, and I like owning them from the first sketch to the 2am production fix.
Eleven-plus years, six industries: hospital EHRs, real-time chat, real estate apps, retail analytics, insurance APIs and enterprise SaaS. Different domains, same itch — take a messy problem and ship something people actually use.
Right now I'm hooked on AI: what happens when LLMs stop being demos and start working inside real products, on real data, under real load.
I believe learning grows by sharing, so I write about what I build on the blog. Call me an explorer in the tech world, always one new tool away from a side project.
Away from the keyboard: running, chasing new places and flying a drone over them. The proof is further down.
Years in software engineering
Industries, from healthcare to enterprise SaaS
Insurance carriers unified behind one API
Countries covered by retail data I helped build
Start from the experience, then pick the simplest tech that delivers it.
It gets tests, fallbacks and monitoring like any other code path.
If I build it, I can debug it at 2am from logs and traces alone.
Terminal
A working shell, for the curious. It knows my experience, my stack and how to reach me.
Workday · Reporting & Analytics
CurrentJava
TypeScript
ReactSQLApache Iceberg
CoverForce · InsurTech
Python
Node.js
React
LLMs
AWS
NIQ (NielsenIQ) · Consumer intelligence
Python
Airflow
Kubernetes
Azure
React
Xome · PropTech
React Native
Node.js
Python
MongoDB
BroadSoft (acquired by Cisco) · Team-One
Node.js
Java
WebSockets
React
Electron
athenahealth · HealthTech
Perl
Ruby
Node.js
CI/CD
Approach
Begin with the user. A clear flow and a well-defined contract between interface and services prevent costly rework later.
Fast, accessible experiences across web, mobile and desktop, with loading, empty and error states designed up front.
APIs are products: explicit contracts, predictable errors and resilience when dependencies fail.
Choose storage for the access pattern, model for the most common queries, and keep migrations safe and reversible.
LLM features earn trust when they are grounded in real data, evaluated continuously and designed to fail gracefully.
Small, frequent releases with automated tests, canary rollouts and one-click rollback — impact visible within minutes.
// Contract first: UI and API teams build in parallel.
export type QuoteStatus = "draft" | "quoted" | "bound";
export interface Quote {
id: string;
carrier: string;
premium: number;
status: QuoteStatus;
}
export function QuoteCard({ id }: Props) {
const { data, error, isLoading } = useQuote(id);
if (error) return <Retry onClick={refetch} />;
if (isLoading) return <Skeleton lines={3} />;
if (!data) return <Empty title="No quotes yet" />;
return <Card quote={data} />;
}
POST /v1/quotes
Idempotency-Key: 7f3c9a2e
Content-Type: application/json
{ "lines": ["WC", "BOP"], "carriers": "all" }
# → 201 Created
# retries with the same key return the same quote
-- Tenant-first index for the most common query.
CREATE INDEX CONCURRENTLY idx_quotes_tenant_status
ON quotes (tenant_id, status, created_at DESC);
SELECT id, carrier, premium
FROM quotes
WHERE tenant_id = $1 AND status = 'quoted'
ORDER BY created_at DESC LIMIT 20;
def extract_submission(doc):
result = llm.extract(doc, schema=Submission)
if not result.valid or result.confidence < 0.8:
review_queue.put(doc) # human in the loop
return None
metrics.record("extraction.accepted")
return result.data
deploy:
steps:
- run: npm test
- run: npm run build
- deploy: canary # 5% of traffic
- watch: error_rate < 0.1%
- deploy: production
rollback: one-click
Selected work
CoverForce · InsurTech
A single request returns real-time commercial insurance quotes from 20+ carriers, ready to compare and bind. Carrier adapters normalise heterogeneous integrations, and LLM-based extraction turns submission documents into structured data, eliminating manual re-entry.
NIQ · Consumer intelligence
The data platform behind NIQ's retail measurement: point-of-sale data from thousands of stores, modelled on Azure into the market-share metrics FMCG brands plan around — orchestrated by an auto-scaling Airflow platform on Kubernetes.
Earlier work
CRM connecting real estate agents with buyers, sellers and relationship teams.
Enterprise collaboration with real-time messaging and video across web, mobile and desktop.
Inpatient EHR for patient history and medication administration.
Appointment scheduling with interactive patient-education screens.
Technology
Beyond the code
Page, Arizona