About this role.
StackAdapt is hiring a Staff Quality Engineer to set quality strategy for AI and agentic products within its Automation and Intelligence Pillar. This senior individual-contributor role builds evaluation frameworks for LLM outputs, agent behavior, safety guardrails, regression detection, and scalable automated testing. The engineer will develop API, UI, integration, and system test tooling integrated with CI/CD while defining quality metrics such as accuracy, latency, cost, and hallucination rates. The role requires 7+ years of hands-on quality engineering and automation experience, strong programming ability, and experience influencing cross-functional teams. Candidates may work remotely from anywhere in Canada or the United States.
Role DNA
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Sample interview questions
I would begin by defining expected user outcomes, unacceptable behaviors, and measurable quality dimensions such as correctness, relevance, safety, latency, and cost. I would create a versioned evaluation dataset containing representative, edge-case, and adversarial prompts; use deterministic checks where possible; and add rubric-based or model-assisted grading with calibrated human review. The framework would run in CI/CD, compare results against baselines, and establish release thresholds for regressions.
I use a risk-based test pyramid. Business rules and edge cases should primarily be covered through fast unit and API tests, integration tests should validate service boundaries and data flows, and UI tests should focus on critical user journeys and browser-specific behavior. End-to-end tests are reserved for high-value release paths because they are slower and more susceptible to environmental instability.
I would first instrument failures to distinguish product defects, test defects, infrastructure issues, and timing problems. I would replace arbitrary waits with condition-based synchronization, isolate test data, remove dependencies on shared state, stabilize external-service interactions with controlled mocks or contracts, and track flake rate as an engineering metric. Retries can reduce transient noise, but I would treat repeated retries as a signal to fix the underlying test or environment.
I would measure task completion rate, tool-call success rate, groundedness or factual accuracy, policy and guardrail violation rate, loop or timeout frequency, human-escalation rate, latency, and cost per completed task. Metrics should be segmented by workflow, model version, prompt version, and input category so teams can identify regressions precisely. I would pair aggregate metrics with curated failure examples to make improvements actionable.
I would participate in discovery and technical planning to turn requirements into clear acceptance criteria, measurable risks, and testability needs before implementation begins. I would make quality visible through concise dashboards, release-readiness reviews, and concrete examples of escaped-defect impact. By providing reusable tooling, practical guidance, and collaborative design feedback, I would make the quality path easier than bypassing it.
StackAdapt is the leading technology company that empowers marketers to reach, engage, and convert audiences with precision. With 465 billion automated optimizations per second, the AI-powered StackAdapt Marketing Platform seamlessly connects brand and performance marketing to drive measurable results across the entire customer journey. The most forward-thinking marketers choose StackAdapt to orchestrate high-impact campaigns across programmatic advertising and marketing channels.
StackAdapt is seeking a talented Staff Quality Engineer to join the Automation and Intelligence Pillar pod, the group building StackAdapt’s AI and agentic products. As the most senior quality engineer on the team, you will set the technical direction for how we test, evaluate, and ship intelligent systems, working across LLM-powered features, agentic workflows, and the data and tooling that support them. This is a hands-on, individual-contributor leadership role: you will lead the effort to design quality strategy for non-deterministic AI systems, build the frameworks and harnesses that make those systems testable, and raise the quality bar across a fast-moving, cross-functional agile environment. Your work will directly affect the success of product releases, accelerate our defect detection and prevention capabilities, and help define what quality means for AI at StackAdapt.
Learn more about our engineering culture here: https://www.youtube.com/watch?v=LXM2NrkhKZc
StackAdapt is a remote-first company; we are open to candidates located anywhere in Canada and the United States for this position.
What You’ll Be Doing:
- Own and drive the end-to-end quality strategy for the Automation and Intelligence Pillar pod’s AI such as our Ivy product, from test architecture through release readiness
- Design and build evaluation frameworks for non-deterministic systems, including LLM output quality, agent behaviour, regression detection, and guardrail/safety testing
- Develop reliable, scalable automated test suites and tooling that address functional, system, API, integration, UI, and regression testing, and integrate them into our CI/CD pipeline
- Establish quality metrics and benchmarks (accuracy, latency, cost, hallucination/failure rates) that give the team confidence to ship and inform data-driven decisions
- Partner closely with Engineering Managers, Product Managers, Designers, ML/Data Science, and other engineering teams to align requirements, priorities, and definitions of done
- Act as a technical mentor and force multiplier across the QE org, promoting QE best practices, driving process improvements, and levelling up testing for AI systems company-wide
- Participate in technical planning, code review, and architectural decision-making, advocating for testability and reliability from the design stage
- Provide timely, actionable test result feedback to the Automation and Intelligence Pillar pod, the QA team, and other relevant stakeholders
What You’ll Bring to the Table:
- 7+ years of professional, hands-on software quality and test automation experience, with a track record of setting technical direction on complex systems
- Deep, hands-on experience with API & UI test automation frameworks such as Playwright, Cypress, Jest, or Junit
- Fluency in at least one of TypeScript, JavaScript, Python, or Java with preference for TypeScript
- Experience testing AI/agentic systems (evals, prompt/regression testing, output validation) and using AI to scale automation (test generation, self-healing tests, failure triage) with technologies such as OpenAI, Anthropic
- Experience with CI/CD tools like Jenkins, Github Actions, or CircleCI
- Strong understanding of scalable system design for web-based APIs and backend processing systems
- In-depth understanding of QA methodologies in a software company with fast release cycles
- Proven ability to define test case design standards and coverage strategy such as edge/negative, compatibility, performance and concurrency scenarios and to own a test case management practice (e.g. TestRail) that others build on
- Knowledge of React, including but not limited to adding data-testids
- Ability to explore a codebase and use technical tools to gain an understanding of technical implementation
- Experience coaching and influencing cross-functional teams on tooling, testing plans and strategies, and guiding them through execution
The compensation range listed for this role reflects the expected base salary for candidates located in the posting country based on a global rate. It is informed by market data and the approved budget for this position. StackAdapt maintains different compensation ranges for roles across other countries and regions, and final offers will be aligned to the candidate’s current location. We do not ask candidates about current or prior salary history, and we will not use such information, if volunteered, in setting an offer.
This range represents base salary only. Depending on the role, candidates may also be eligible for additional compensation such as annual bonuses, commissions, equity awards, and a comprehensive benefits package.
Factors Influencing Final Compensation:
- The final compensation offer will be determined by a variety of factors, which may include, but are not limited to: the candidate’s specific experience, technical skills, knowledge, abilities, and relevant education, licensure, and certifications.
- Other business factors, such as organizational needs and budget alignment, may also be considered in the final offer.
Canada Base Salary Band
$134,400—$184,800 CAD
USA Base Salary Band
$136,000—$187,000 USD
StackAdapter’s Enjoy:
- Highly competitive salary
- Retirement/ 401K/ Pension Savings globally
- Competitive Paid time off packages including birthday’s off!
- Access to a comprehensive mental health care program
- Health benefits from day one of employment
- Work from home reimbursements
- Optional global WeWork membership for those who want a change from their home office and hubs in London and Toronto
- Robust training and onboarding program
- Coverage and support of personal development initiatives (conferences, courses, books etc)
- Access to StackAdapt programmatic courses and certifications to support continuous learning
- An awesome parental leave program
- A friendly, welcoming, and supportive culture
- Our social and team events!
Please note: Benefits and perks may vary depending on your country of employment and the nature of your engagement. In locations where StackAdapt does not have a legal entity, employment and benefits are administered in accordance with local regulations and partner policies.
StackAdapt is a diverse and inclusive team of collaborative, hardworking individuals trying to make a dent in the universe. No matter who you are, where you are from, who you love, follow in faith, disability, superpower status, ethnicity, or the gender you identify with (if you’re comfortable, let us know your pronouns), you are welcome at StackAdapt. If you have any requests or requirements to support you throughout any part of the interview process, please let our Talent team know.
We use artificial intelligence (AI) to streamline the resume reviews of candidates and assess their fit based on the criteria outlined in the job posting. We do not use AI to make any final hiring or interview decisions.
About StackAdapt
We’ve been recognized for our diverse and supportive workplace, high performing campaigns, award-winning customer service, and innovation. We’ve been awarded:
G2 Top Software for 2026
2026 Best Workplaces™ for Young Talent and in Canada by Great Place to Work®
#1 DSP on G2 and leader in a number of categories including Cross-Channel Advertising
2026 Winner in the (CTV/OTT) Product/Platform category for the 2026 ADWEEK Tech Stack Awards
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