AUTOMATION ARCHITECTURE · QA LEADERSHIP · HEALTHCARE
Quality is a clinical requirement, not a checkbox.
QA lead for a cardiovascular diagnostics platform — automation architecture, clinical data validation, release sign-off.
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Years in quality engineering
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Automation suites designed & built
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Automated tests authored
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Promotions in one organization
// about
I started as a QA intern in 2017 and never treated testing as a stepping stone to development — quality engineering is the engineering discipline I chose. At Mindfire Solutions I progressed through every level of the QA ladder, from writing my first automation scripts as a trainee to leading the testing function for the largest healthcare release in my program's history.
All nine years have been in US healthcare — three products spanning the care continuum: a chronic care management platform, a post-acute care transitions platform later acquired by a Fortune 5 healthcare organization, and currently a cardiovascular diagnostics platform for a US-based medical imaging client. The current work means a kind of testing most QA engineers never do — reconciling clinical computation outputs across CSV exports, API payloads, and generated PDF reports, and tracing discrepancies to underlying computation conventions instead of dismissing them as expected behavior.
My philosophy: stress-test, don't validate. A QA function that exists to confirm the happy path is overhead; one that finds what everyone else assumed was fine is leverage. I apply the same standard to AI tooling — which I use aggressively in my QA workflows, and verify ruthlessly.
// skills
Every skill is labeled with how I actually use it. No padded lists — that's the same honesty standard I hold a test report to.
TypeScript/JavaScript-stack automation: framework architecture, Page Object Model, data-driven patterns, visual regression, flake reduction.
REST endpoint validation from schema to data contract — including parity checks against exports and UI state.
Backend verification and clinical data reconciliation across CSV, API, and report outputs.
Suites wired into pipelines, version control discipline, and test-cycle management at scale.
The strategy layer: planning what to test, proving what was tested, and owning the release decision.
Not a buzzword — internal tooling in production use by my team.
// automation architecture
Fifty-plus suites taught me that automation succeeds or fails at the architecture level, not in individual tests. This is the anatomy I build to.
e2e-framework/
├─ config/ env- & jurisdiction-aware settings
├─ fixtures/ seeded, anonymized clinical data
├─ pages/ Page Object Model (TypeScript)
├─ api/ request layer · contract & parity checks
├─ db/ SQL / Mongo verification helpers
├─ visual/ baseline snapshots · diff review
├─ reporters/ Zephyr sync · Slack summaries
└─ ci/ GitHub Actions · parallel shards
// experience
Nine years at Mindfire Solutions across the US care continuum — chronic care management, post-acute care transitions, and now cardiovascular diagnostics. A ladder climbed through delivery, not job-hopping.
I joined this engagement with zero medical-imaging background — coronary CT scans, plaque morphology, vessel territories, FFR were a foreign language. The choice was to stay a button-clicking outsider or learn the domain deeply enough to question the platform's numbers. Two and a half years later, I lead its testing function — promoted to Testing Team Lead while embedded on this project.
Technology-enabled chronic care management platform helping payers and providers engage rising-risk patients between visits — improving outcomes before patients become high-acuity. First engagement as Associate Test Lead.
Post-acute care management platform — care transitions and clinical decision support for Medicare Advantage populations, on a Java microservices architecture. The client was later acquired by a Fortune 5 healthcare organization.
Jun 2026 — PresentCURRENT
Mindfire Solutions
Promoted while embedded on the cardiovascular imaging engagement — now leading its testing function. Full record in the engagement card above.
Mar 2022 — Jun 2026
Mindfire Solutions
Promoted into the lead role and assigned the chronic care management engagement; after delivering it, moved to the cardiovascular imaging client in Oct 2023 — and earned the Team Lead promotion on that project.
Jan 2019 — Mar 2022
Mindfire Solutions
Large-scale automation ownership and CI/CD integration on the post-acute care engagement — the longest client relationship of my tenure.
Jan 2017 — Jan 2019
Mindfire Solutions
Foundations: automation scripting, API testing with Postman, database testing, and CI/CD process discipline.
// case studies
Six representative cases from a regulated medical-imaging platform — each one a problem, an approach, and a verifiable outcome.
Largest release in program history
Problem · A clinical-grade platform's biggest-ever release: massive regression surface, clinical correctness requirements, and coordinated DEV/QA workflows.
Outcome · QA lead with sign-off accountability for the program's most consequential ship.
Defect vs. convention — correctly distinguished
Problem · Per-territory aggregations in PDF reports didn't match CSV-derived sums for FFR / plaque-volume data.
Outcome · Prevented both a false bug report and a silently shipped data inconsistency. In clinical software, 'the numbers don't match' is the start of analysis, not the end.
2 ship-blocking defects caught pre-release
Problem · A new work-item summary CSV export endpoint needed end-to-end validation before release.
Outcome · Caught the endpoint returning HTML instead of CSV (routing misconfiguration) and duplicate work-item records in export output.
Regulatory-relevant catch
Problem · Switching jurisdiction on the export-creation screen failed to reset the in-progress export list — a data-isolation risk in a regulated, multi-jurisdiction product.
Outcome · Data-isolation defect caught in QA rather than in production, in a domain where jurisdiction boundaries are a compliance requirement.
Internal tooling in team use
Problem · Manual Zephyr Scale cycle auditing and daily status reporting consumed recurring lead time.
Outcome · Recurring audit and reporting work automated — engineering contribution beyond test execution, adopted by the team.
RCA traced to a specific PR
Problem · A production crash needed tracing to its source in a complex imaging-pipeline dependency chain.
Outcome · Release-validation checks strengthened around dependency changes.
// qa dashboard
Every number on this page is evidence-backed — no estimated percentages, no invented coverage figures. That's the same standard I hold defect reports to.
// credentials
Certification
Anthropic
Award
Mindfire Solutions
Education
College of Engineering and Technology, Bhubaneswar · 2014–2017
Education
Samanta Chandra Sekhara Autonomous College · 2011–2014
// contact
Open to senior QA leadership, SDET, and quality strategy roles — particularly where software quality has real-world consequences.
Bhubaneswar, Odisha, India
References and detailed recommendations available on request — including development leads and client-side stakeholders I've shipped releases with.