• Leading dental Autopilot system in a $40B global healthcare industry — operating across 28 countries, live in production
• Multiple in-house AI teams building proprietary models — not just consuming APIs. Claude, Cursor, Luvable, and LLM-powered workflows are part of the daily stack
• Manila is not a back office. It is the delivery engine — operations, AI, product, and engineering all run from here. Your work ships globally
• We promote based on output, not tenure. The people who move fastest here are the ones who own their work completely
• 300+ people and growing — the career path is real because the company is growing into it

“This role isn’t about the product itself or whether a button is working. It’s about whether what we built works for the people using it. Your job is to stay close to end users and continuously surface the gap between what we shipped and what they truly need. If your instinct is to simply tick tasks off a checklist or validate if a button is working, this isn’t for you. We’re looking for someone who treats quality as a system - and asks the harder question: did we solve the right problem?”

— Des, CTO / GM, EviSmart Manila

WHAT YOU’LL OWN

• Quality intelligence for the live production system— you analyze production, staging, and test data to surface patterns, anomalies, and early warning signals before they become incidents. This is your primary output. - The quality metrics and system health indicators that actually reflect risk— you design and own the indicators that answer "where is fragility accumulating" — not pass/fail counts, but signals that mean something to engineering. - Systemic root cause investigations— when defects recur, you own the investigation end to end. Recurring failures don't get closed in your queue. They get fixed at the source. - Engineering partnership on assumptions and regressions— you work directly with engineers to validate their assumptions, challenge incomplete fixes, and prevent regressions at the system level before they ship. Not after. - Tooling and dashboards that make quality visible— you build the lightweight queries, scripts, or dashboards that give engineering and operations a shared view of system health. If it can't be seen, it can't be managed. - You are the first to know where the system is becoming fragile— when a pattern signals hidden risk, you surface it before it reaches production. Nothing waits for a report. Nothing escalates that could have been caught earlier. WHAT YOU’LL GET

• A seat at the AI table — work directly alongside in-house AI model teams using Claude, Cursor, Luvable, and LLM-powered workflows. You'll work with these tools daily, not read about them in a newsletter

• Global reach, Manila-built — EviSmart operates across 28 countries. Your work lands across the dental industry in North America, Europe, and beyond — from your desk in Manila. - Your metrics, your dashboards, your risk signals — when the system holds under pressure across 28 live markets, that outcome has your name on it

• Career path: Intelligence Engineer → Senior Intelligence Engineer → Quality Engineering Lead. The roles exist because the system we're building is growing into them.

• Above-market compensation: Up to 200,000 PhP salary for candidates who have personally owned quality outcomes in a live production environment.

• HMO coverage, 13th month pay, and all government-mandated benefits

HOW WE WORK

We share work before it's ready. We debate decisions loudly and execute them quietly. We default to fixing problems instead of escalating them. Manila is the delivery engine for a global platform — the standard is high and the pace is real. A problem that sits for 48 hours is a retention problem. An ambiguous requirement is a build problem. We fix things before they escalate, and we expect everyone here to do the same. If you've spent time waiting for permission to solve something obvious — you'll notice the difference on your first week. "Why EviSmart and not a bigger company? Because at a bigger company, your work goes into a queue. Your output is handled by a template. Here, what you build ships to 28 countries. That's the kind of ownership most roles never give you — and we think the best people want it."

— EviSmart Talent Team

A NOTE ON WHAT WE’RE NOT

If your title is "QA" but your instincts are engineering — read this carefully. This role is not a rebrand of manual testing, UAT sign-off, or test case execution. If your primary experience is writing predefined scripts and running regression suites, this is not a match — and we'd rather say that clearly here than waste your time in an interview. What we are hiring for is closer to a production intelligence function: someone who treats quality as a system property, works from data, and partners with engineering as an equal. The title is new because the function is new. That's the point. This is not a cost-center role and Manila is not a support function. Our Manila team leads engineering and operations — the product ships from here. If you've seen 'Philippines office' mean something smaller at other companies, that is not what this is. On AI: EviSmart's AI is not a marketing claim. We have in-house model research and development teams, and the tools we use daily — Claude, Cursor, Luvable, LLM-powered workflows — are part of the actual stack, not a slide in a deck. The next 12 months will see expanded AI-generated output across dental design automation — and this role sits at the center of defining what "correct" looks like for a model, not a spec sheet. That standard doesn't exist yet. You build it. WHAT WE NEED

• 2–5 years in quality engineering, SRE, data analytics, production support, or a closely related function in a SaaS or software environment— where you personally owned quality outcomes, not just executed test plans someone else wrote
• A track record of identifying systemic failure patterns end to end— from signal detection to root cause investigation to confirmed fix. You can walk us through the before and after in the interview. - Hands-on comfort working with data— SQL queries, log analysis, metrics dashboards, or equivalent. You can answer "where is risk accumulating" with data, not intuition alone. - Engineering mindset with systems thinking— you reason about cause and effect across complex systems, challenge assumptions before they become defects, and ask uncomfortable questions early
• Communication that is clear, fast, and written — we are distributed and async writing is a core skill, not a soft one
• Background in software engineering, data engineering, SRE, platform or infrastructure engineering, or systems engineering with strong data exposure is a strong advantage

Apply at https://job-boards.greenhouse.io/evismart

EviSmart • Philippines • evismart.com