Lead Software Development Engineer in Test (SDET)

About the Role:

If you want to build, develop, and see your impact, join Skillz and level up your Career!

Skillz is fueled by FIRY (NYSE: FIRY), a founder-led technology portfolio building the durable infrastructure of competition across gaming, intelligence, identity, payments, and commerce. Within the FIRY ecosystem, Skillz is focused on competitive mobile gaming and trusted player experiences.

Skillz, the first publicly-traded mobile eSports platform that hosts billions of casual mobile gaming tournaments for millions of players worldwide, is revolutionizing the gaming industry. By fostering social competition within games, the Skillz platform helps developers build multi-million dollar franchises by enabling real-money activity in their games and providing operational support while connecting players through fair, enjoyable, and meaningful competition.

At Skillz, we understand the thrill of achievement and the satisfaction of overcoming challenges. Want to join a team made up of alums from Apple, Amazon, Google, Microsoft, Tesla, Twitter (X), Roblox, Zynga, Samsung, Lyft, EA, Riot, Nexon, Gameskraft, PlayStation, Unity, Scopely, Tinder, Intel, Deloitte, EY, Twitch, DraftKings, Wynn Resorts and more? Learn more to see if Skillz is the right fit for your next career move!

What You’ll Own:

The Lead Software Development Engineer in Test (SDET) role is critical in driving engineering-led quality by ensuring the reliability, scalability, and performance of our products. This role contributes directly to customer experience, release confidence, and overall product stability through strong automation practices and proactive quality ownership.

By strengthening test automation, CI/CD integration, and defect prevention strategies, this role will significantly reduce production defects, improve system stability, and accelerate development velocity.

What You’ll Do:

• Design, build, and maintain scalable automation frameworks for UI, API, integration, and backend testing.
• Integrate automated tests into CI/CD pipelines, improve pipeline efficiency, and establish effective release gates.
• Improve test environment reliability through better environment management, test data practices, and flaky test reduction.
• Lead performance testing, including load, stress, and scalability testing; identify bottlenecks and work with engineering teams on solutions.
• Debug complex failures across distributed systems and services, lead root cause analysis, and help prevent recurring issues.
• Use AI coding assistants and LLM-based tools, such as Claude, Cursor, or Copilot, to improve test design, expand coverage, generate tests, analyze failures, and accelerate debugging.
• Apply AI- and ML-assisted techniques to log analysis, failure clustering, test optimization, and defect pattern detection.
• Partner with DevOps and SRE teams to improve observability, deployment stability, and service reliability.
• Mentor SDET and QA engineers, guide technical execution, and promote strong testing practices across teams.
• Apply testing fundamentals across functional, regression, system, and end-to-end testing.

What You’ll Bring:

1. 10 years of experience in software quality engineering, with at least 3+ years in a technical leadership role
2. Strong hands-on experience in building scalable test automation frameworks for UI (Appium), API, and backend systems
3. Deep experience working with CI/CD pipelines (Jenkins, GitHub Actions, etc.), including test integration, pipeline optimization, and release gating
4. Strong understanding of infrastructure components impacting quality (cloud environments, containers, microservices, service dependencies, and test environments)
5. Proven experience ensuring environment stability, including test environment reliability, test data management, and flaky test reduction
6. Strong background in performance testing and engineering (load, stress, scalability testing, and performance bottleneck analysis)
7. Experience collaborating with DevOps/SRE teams to improve system reliability, deployment stability, and observability
8. Hands-on experience leveraging AI tools such as Claude, Cursor, Copilot, and LLM-based systems to improve test design, automate test creation, analyze failures, and accelerate debugging workflows
9. Experience applying AI-driven approaches for log analysis, failure clustering, test optimization, and defect pattern detection

Note: Ability to work from the Ba…