sdlc-skills
Agent skill packs for lifecycle work that is easy to fake and hard to verify: false-green tests, mutation gates, incidents, design decisions, release judgment.
QA Architect & Lead SDET with 10+ years engineering AI-powered testing systems at scale. Previously spent 3+ years (2021–2024) driving quality at Mendix — where releases shipped without fear.
Python · Playwright · AI Automation · CI/CD · Cloud-Native · Microservices
I started where most engineers start — writing code, shipping features, wondering why things kept breaking in ways nobody anticipated. That question became an obsession.
Over 10+ years across SaaS platforms, telecom infrastructure, and cloud-native microservices, I've moved from writing tests to designing the systems that make entire teams confident in every release.
Today I work as a QA Lead — embedding quality into products from day one, building automation that evolves with the application, and introducing AI where it genuinely reduces noise rather than adding hype.
I don't take on projects where I'll be writing tickets. I take on projects where I can change how quality works.
// how I engage
Design scalable UI, API, and E2E frameworks from scratch — built to survive real teams and real velocity.
Self-healing selectors, AI-assisted test generation, and intelligent failure triage — less maintenance, more signal.
Testing embedded into every pipeline stage — not as a gate, but as a continuous confidence signal.
Cloud-native microservices, telecom infrastructure, device firmware — I've tested systems where failure isn't an option.
Quality KPIs, coverage dashboards, and real-time failure intelligence — decisions driven by data, not gut feel.
Define testing standards, mentor engineers, and embed a quality culture across distributed teams.
Every metric here reflects real engineering decisions with real business consequences — not vanity numbers.
CI/CD-integrated testing I built at Mendix cut deployment time across its cloud-native pipelines.
Built end-to-end, API, and UI test suites covering critical paths across microservices.
Self-healing mechanisms and observability-driven analysis cut test instability.
Continuous quality engineering across telecom, SaaS, and cloud-native platforms.
Defined and drove QA standards and mentored engineers across distributed teams at Mendix.
DOCSIS, TCP/IP, firmware validation on millions of broadband devices at Liberty Global.
"Most teams don't have a testing problem. They have a confidence problem in their releases."
This is my mental model. Every system I design moves quality from reactive to predictive — from manual to self-governing.
AI risk analysis predicts which tests to run, reducing execution time by targeting high-impact areas.
Self-healing selectors and adaptive locators reduce maintenance to near zero — tests evolve with the app.
Observability integration means failures surface with context, not just stack traces — faster root cause.
Not just tools — systems thinking across automation, AI, infrastructure, and observability.
Whether you're a QA engineer leveling up, a team that needs a framework audit, or a leader who wants a clear quality strategy — here's how we can work together beyond a full-time hire.
For QA engineers ready to move beyond writing tests. We work on architecture decisions, career strategy, code reviews, and the mindset shift that separates testers from architects.
I audit your existing test suite — architecture, flakiness patterns, CI integration, coverage gaps. You get a written report with a clear remediation roadmap, prioritised by business impact.
A hands-on half-day or full-day session for engineering teams. Covers AI-driven test generation, self-healing automation, CI/CD quality integration, and observability-driven QA. Remote or on-site.
A focused 90-minute session where I dig into your product, your release process, and your quality pain points — and hand you a concrete strategy: what to build, what to fix, what to stop doing.
Topics I cover
One post a week. Real engineering decisions, specific tools, and the hard lessons from building AI-powered testing systems at scale.
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These aren't responsibilities lifted from a job description. They're outcomes from a decade of engineering decisions.
Most engineers start writing tests on day one. I start by understanding the release pipeline, failure patterns, and what confidence actually means for your product.
Self-healing locators, adaptive test structures, and AI-assisted maintenance mean your test suite evolves with your product — not against it.
Testing as a gate is too late. I design quality into every stage of the pipeline so problems surface in seconds, not sprint reviews.
Broadband firmware at Liberty Global. Cloud-native SaaS at Mendix. When stakes are high and failures are public, I've been the engineer who made sure they didn't.
Real AI workflows: test generation from specs, failure analysis from logs, coverage mapping from usage data. Not demos — shipped systems.
Mentoring, standards, frameworks, code reviews — I raise the automation ceiling for every team I join. The knowledge doesn't leave when I do.
I can explain a flaky test to an architect and explain business risk to a CPO. I bridge the gap between technical quality and strategic confidence.
Infosys → Liberty Global → Mendix → QA Lead today. Each role was a deliberate step forward in complexity, scope, and impact. I don't plateau.
If you're building something that has to work — let's talk.
Whether you're hiring, booking a session, or just want to talk quality strategy — I'm easy to reach.