Senior Software Engineer in Test / SDET (AI-native)

Leapsome; United States; Hybride; USD 78 000 - 117 000; Plein temps

Avantages offerts par ce poste

Learning budget

Work-from-home stipend

Equity

Vacation days

Résumé du poste

Leapsome is hiring a QA Engineer to own the quality of our LLM-powered features and help build an AI-native SDLC. You will drive eval coverage, gate features, and coach squads to write tests and evals for their own features, embedding quality into every team.

You will develop our AI QA agent and autonomous systems, define risk tiers with product/design/engineering, and ensure CI is fast, cost-efficient, and trustworthy while guarding sensitive customer data.

Qualifications

• Software engineer who specializes in quality and writes production-quality TypeScript.
• Build systems that automate and improve testing, and encode fixes into agents.
• Strong eye for UI/UX; raise flow inconsistencies early in specs.
• Experience with evals for LLM features and AI agents.
• Experience running AI agents for testing or review in a team.
• Maintain a high bar for customer data privacy and security.
• Think in terms of risk, evidence and cost while improving quality and speed.
• Have led engineering teams in elevating quality practices.

Responsabilités

• Own the quality of our LLM-powered features: eval coverage per feature, validated datasets, a gate every new AI feature passes before it merges, and clear routing to the owning squad when an eval fails
• Coach squads to write and maintain evals and tests for their own features, so quality is built into every team
• Develop our AI QA agent and other autonomous systems as a product: benchmark specs, regression protection, fast cloud runs, and repeatable release checks
• Define risk tiers with product, design and engineering to decide verification levels
• Make CI fast, cost-efficient and trustworthy: manage runner/model cost, pipeline duration, and fix flaky tests
• Refine our quality standards in the skills and rules our coding and review agents follow
• Review specs for testability before development starts, including MCP server or agent actions
• Measure quality with metrics like escaped defects, severity, and agent/evals reliability

Connaissances

Quality engineering

TypeScript

UI/UX

LLM evals

AI testing

Automation

Outils

Playwright

Playwright MCP/CLI

Vitest

Mocha/Chai

GitHub Actions

Description du poste

What is Leapsome? Leapsome is the AI-powered people platform revolutionizing HR for modern teams. Leapsome drives HR excellence and empowers high-performing teams by automating, connecting, and simplifying every HR process across the employee lifecycle: from onboarding and performance management to engagement and development. Built with ease of use in mind, our platform ensures high adoption by employees, managers, and People teams alike.

Our purpose is to make work fulfilling for everyone, and our vision is to reshape the future of work by being the leading People platform for HR excellence and high-performing teams. We enable companies to create environments where people can achieve their goals, learn and grow together, and build genuine motivation & engagement.

Trusted by thousands of organizations globally, Leapsome secured $60 million in Series A funding led by Insight Partners in March 2022. This funding allowed us to further develop our intelligent platform, create exceptional employee experiences, and expand into the US market.

It’s an incredibly exciting time to join Leapsome and be part of reshaping the future of work!

Your Opportunity:

Leapsome builds most of its code with AI agents. Cross-functional squads of product engineers own their features end to end and ship at a pace that would have needed a far larger team a few years ago. Speed only counts if quality keeps up. Our customers trust us with performance reviews, compensation and personal employee data, so every change has to earn its way to production.

QA at Leapsome is a small, senior team inside Product & Engineering, led by our Engineering Manager for QA. We build and run the quality system the whole department works with: an AI QA agent engineers run against their pull requests and staging, eval suites that gate our LLM features, layered automated code review that assesses every change by risk, and the CI pipeline everyone depends on. Engineers across squads contribute to these tools. We own their direction and the standards they enforce.

We are working towards an AI-native SDLC, where every change gets the depth of verification its risk calls for. Automated tests and AI review run on every change, with agent-driven testing and evals wherever they apply. Changes touching permissions, compensation data and other sensitive areas get dedicated human review and testing on top. You will help extend and mature that system, set the bar it has to meet, and define the evidence we need before we rely even more on it.

You will:

• Own the quality of our LLM-powered features: eval coverage per feature, validated datasets, a gate every new AI feature passes before it merges, and clear routing to the owning squad when an eval fails

• Coach squads to write and maintain evals and tests for their own features, so quality is built into every team instead of checked at the end

• Develop our AI QA agent and other autonomous systems as a product: benchmark specs it has to pass, regression protection for every change to the agent, cloud runs fast and affordable enough that engineers use it on every relevant pull request, and repeatable release checks moved to it so release testing focuses on judgment, edge cases and readiness

• Define, together with product, design and engineering, the risk tiers that decide how much verification a change needs, from automated checks to extended testing and human review

• Make CI fast, cost-efficient and trustworthy: runner and model cost, pipeline duration, and flaky tests fixed systematically

• Refine our quality standards in the skills and rules our coding and review agents follow, so recurring issues are prevented at the source

• Review specs for testability before development starts, including capabilities that ship through our MCP server or as agent actions

• Measure quality with metrics that hold up as delivery speeds up: escaped defects, their severity, and the reliability of our agents and evals alongside more traditional KPIs

What is the Technology Stack?

• Core: TypeScript, Node.js, Vue.js, MongoDB

• Testing: Playwright and Playwright MCP/CLI (E2E and as the browser for our QA agent), Vitest, Mocha/Chai

• AI in our SDLC: Cursor (including cloud agents and automations) and Claude Code, agent skills and rules shared across both, layered LLM code review in CI

• AI evals: eval suites per LLM feature, supported by LangSmith, running on relevant changes and as scheduled full runs

• Infrastructure and observability: GitHub Actions, Docker, AWS, Datadog (including CI visibility), Mixpanel

• Collaboration: Notion, Slack, GitHub

You’ll be a good fit if you:

• See yourself as a software engineer who specializes in quality: you write production-quality TypeScript, build tools other engineers rely on, and debug down to the root cause, from a flaky test to a production issue

• Build systems that compound rather than running the same manual loop again: the second time you fix something, you automate it, encode it in an agent skill or remove its cause

• Have a strong eye for UI and UX: you notice when a flow is confusing or inconsistent, and raise it while it is still a spec or a prototype

• Have built or owned evals for LLM features and can tell a bad model output from a bad dataset

• Have run AI agents for testing or review in a team, and know where they fail and how to close the loop to prevent drift

• Hold a high bar for anything that touches customer data, and can show how a system meets that bar

• Think in risk, evidence and cost rather than coverage percentages, and act on it proactively: you spot where quality, speed or spend is slipping, from model choice to CI minutes and agent runtime, and fix it

• Have changed how an engineering team works, not only what it tests, and want to keep reinventing how quality is done

Benefits

• Learning and development: Grow your skills with a €2,000 yearly development budget and full access to the Good Habitz platform.

• Work-from-home stipend: A one-time €1,000 stipend to set up your home workspace.

• Competitive pay and equity: Competitive salary plus a pre-IPO equity package, so you share in the company's growth.

• Corporate benefits: Exclusive discounts and deals from our partner network.

• Vacation: 30 vacation days a year plus public holidays, with the option to upgrade to 40 days at adjusted pay. After 5 years at Leapsome, take a month-long paid sabbatical.

• Wellness benefits: Stay active with a fully sponsored Urban Sports Club M membership, and support your mental health with an Oliva subscription that includes 1:1 therapy sessions, plus company workshops on mindfulness and digital wellness.

• Hybrid and flexible work: Spend 2 days a week with the team in our Berlin office, Tuesdays and Thursdays.

• Impact: Join a fast-growing HR platform trusted by more than 2,000 companies worldwide: you'll help shape how companies run HR and grow their people in one connected system.

• Culture: A diverse, international team that values open feedback and celebrates wins, big and small.

• Sponsored lunch: Lunch is on us every Tuesday and Thursday.

• Work from anywhere: Work from a different location for up to 2 months a year.

• Monthly team activities: Join Feierabend, a monthly budget to get-together in Berlin — hosted by employees, for employees.

This role is based in Berlin and the salary range for this position is €70,000 - €105,000 + Bonus + Equity. View our full compensation framework here. Leapsome aims to pay generously and fairly. If the listed range isn’t working for your situation, please tell us early in the process, we’d rather have that conversation than lose a great candidate over a number we may be able to address. If your role or skillset isn’t covered in our compensation framework, it’s likely because we haven’t hired enough in that area yet. We’ll build a data-backed range before we make you an offer, and we’ll share our thinking with you as early as we can. This note is published for transparency. It reflects our compensation philosophy as of June 2026 and describes our general global approach — it is not a contract, offer, or entitlement to any salary, increase, or bonus, and may change at any time. Individual compensation is always governed solely by your written employment agreement and applicable local law.

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply for jobs unless they meet every qualification. If you’re excited about this role but your experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.