Quality
QA, automation, API validation, and systematic problem-solving.
QA Engineer, AI Video Creator, and Sales Researcher combining technical precision, creative execution, and clear communication.
QA Engineer • AI Video Creator • Sales Research
QA Engineer•AI Video Creator•Sales Research
I test software for a living, and bring the same discipline to AI video and lead research.
My foundation is quality engineering and software testing — automation, embedded systems, troubleshooting, and data-driven validation. That discipline shapes how I work: understand the problem, validate the details, and deliver with purpose.
I apply the same mindset to AI video creation and sales research — from short-form scripting and editing to prospect research, ICP matching, lead qualification, and outreach preparation.
QA, automation, API validation, and systematic problem-solving.
AI-assisted short-form video, scripting, storyboarding, and editing.
Prospect research, ICP matching, lead qualification, and outreach preparation.
Different disciplines. One approach: understand, improve, deliver.
Engineering, creative, and research tools I use across QA, content production, and remote collaboration.
Testing, automation, APIs, embedded systems, and release workflows.
AI-assisted scripting, video production, editing, and publishing.
Prospect research, documentation, reporting, and remote collaboration.
Workflow first. Tool second.
Whether I’m testing software, creating AI content, or researching prospects, I use the same structured approach: understand the problem, work from evidence, validate the details, and deliver clearly.
Clarify the goal, requirements, audience, constraints, and expected outcome before starting the work.
Gather evidence, explore scenarios, investigate edge cases, and challenge assumptions.
Create the test, automation, content, workflow, or research output needed to solve the problem.
Check quality, behavior, accuracy, consistency, and whether the result actually meets the intended goal.
Package the work clearly, communicate the result, and improve it through feedback when needed.
Real QA case studies, published affiliate reels, and a structured sales-research workflow.
A Taglish family short built entirely from AI-generated clips: script, scene prompts, six 8-second generations, edit, captions, cover. Published as a Facebook Reel.
Original series, not client work. Every frame is AI-generated from written prompts; the characters, home, and story are fictional. Published on the Pamana Natin Facebook page, 28 Sep 2026.
ATTACH: approved Still 1 as start frame START STATE: Isko sits on the gray sofa frame-right, holding the blue-cased tablet, pouting at the screen. PRIMARY ACTION: Isko shakes the tablet twice, then turns its screen toward camera-left, toward his unseen father, and looks that way. SECONDARY REACTION: His lower lip trembles. The tablet screen shows only a small spinning loading circle on a dark background — no text, no logos. ISKO VOICE: Small 3-year-old Filipino boy's voice, high and soft, slightly unclear toddler consonants, short simple words, native Tagalog, never adult phrasing. ONLY ISKO SPEAKS: "Pa… wala YouTube." PERFORMANCE: slow and sad, toddler pout, small breath before "wala." CAMERA: medium-close, slow gentle push-in. END STATE: Isko holds the tablet out toward camera-left, pouting, eyes on his off-screen father. IDENTITY LOCK: keep Isko's face, cowlick, skin tone, and toddler proportions exactly as the start frame. No beautify, aging, or redesign. WARDROBE LOCK: light-yellow dinosaur t-shirt, blue shorts. PROP LOCK: black tablet in chunky blue rubber case, same size throughout. LOCATION LOCK: same sofa, walls, and light as the start frame. NEGATIVE: no subtitles, no on-screen text, no background music, no extra people, no face morphing, no logos.
Start state → action → end state, four locks as invariants, and a negative list. The same shape as a test case — which is why the cast and room hold across all six clips.
▶ Play EP1 · 0:58 · Facebook Reel
EP2 is in production. Published product reels and the AmpX spec creative are in the AI Creative Gallery below.
Invented "Waypoint," a B2B SaaS delivery-visibility tool, to run the full Researcher → Lead Generator workflow end to end — an ICP Card and a 10-company lead sheet against real, publicly known businesses.
⚠ Portfolio sample — not a real client engagement. "Waypoint" is fictional; the 10 target companies are real, publicly known businesses used only to show realistic ICP-matching. No personal contact data was collected — company-level only.
| Market | Mid-market B2B SaaS (100–800 employees) running 3+ agile engineering squads across Jira/Linear + GitHub + Slack. |
|---|---|
| Vehicle | A delivery-visibility dashboard that auto-syncs sprint, PR, and deploy data from tools already in use. |
| Outcome | Cuts weekly sprint-status reporting from ~2–3 hrs/EM to under 15 minutes. |
Manual status roll-ups across Jira/GitHub/Slack · cross-team risk found too late · leadership can't answer "are we on track" without pinging 4–5 EMs.
Recent Series B/C/D funding · actively hiring EM/Dir/VP Engineering · engineering blog post about scaling.
Verdict: HUNGRY. A funded, established competing category (LinearB, Jellyfish, Swarmia) proves real budget already moving toward this problem.
| Company | Employees | Target role | Trigger | Temp. |
|---|---|---|---|---|
| Render | ~209 | VP/Dir. Engineering | 3+ live EM reqs; $100M Series C ext. Feb 2026 | Hot |
| Temporal Technologies | ~430–611 | VP/Head of Engineering | $550M Series E, 2026-09-14 (~2 wks old) | Hot |
| Supabase | ~280+ | Engineering Manager (multi-req) | Multiple live EM reqs, Sep 2026 | Hot |
| Coder | ~634–644 | VP/Dir. Engineering | $90M Series C, 2026-04 (~5–6 mo old) | Warm |
| incident.io | ~101–250 | Dir./VP Engineering | $62M Series B, 2025-04 (~17 mo old) | Warm |
| PostHog | ~200–224 | Head/VP Engineering | Series E Sep 2025 (~1 yr old) | Warm |
| LaunchDarkly | ~581–664 | VP/Dir. Engineering | No 2026 round found — fit strong, trigger weak | Warm |
| Retool | ~447 | VP/Dir. Engineering | Last funding 2022 — no fresh trigger found | Warm/Cold |
| Sourcegraph | ~138–194 | VP/Head of Engineering | Last funding 2021 — no trigger found | Cold |
| Linear | ~118–203 | (would-be: Head of Eng.) | Screened out — own hiring page says "hire slowly, stay small"; opposite of this offer's pain. | Not pursued |
Selected AI-assisted creative work: an original narrative series, short-form product and affiliate videos, UGC-style concepts, and e-commerce advertising.
Original series
Spec work
Spec work
Send me your product or role. You get one finished piece — a reel, an ad, a bug report, or a qualified lead list — in your brand's voice, with a note on how I checked it. Before we ever talk rates.
Request a spec sample →Recommendations shared publicly on LinkedIn.
▶
Watch reel ↗
An original Taglish family short, every frame AI-generated from written prompts — script, scene prompts, generation, edit, captions, cover, publish.
10+ years across enterprise web, Android, and automotive embedded QA, newest role first.
Owned feature QA from planning through release readiness, including BrowserStack validation, Postman API testing, JIRA triage, and TypeScript automation.
Led infotainment automation, configured remote test environments, ran endurance/performance testing, and converted Android VTS cases to PyTest.
Automation scripting, test-environment troubleshooting, model-based test design, and result analysis across enterprise delivery.
White-box and black-box testing against client requirements, custom JIRA workflows and defect management, and Jenkins and VBA tooling for reporting and time tracking.
Open to remote roles and projects in QA & Software Testing, AI Video Creation, and Sales Research / Lead Generation. If there’s a fit, let’s talk.