Principal Engineer, Quality Platform

is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates,  empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products—
Performance (affiliate),
Creator (influencer), and Advocate (customer referral)—unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust,  helps brands show up where it matters most. Today, over 5,000 global brands, including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics, rely on  to power more than 225,000 partnerships that deliver measurable business results.

• Own the multi-quarter technical vision, architecture and roadmap for the QA platform.
• Turn ambiguous, cross-team quality problems into clear technical direction, including ones nobody has fully defined yet.
• Decide what to build, buy, adopt or retire, and when a problem deserves something purpose-built.

• Write code and prototype the hardest parts yourself, especially where the problem is new or the risk is high.
• Own what you ship in production: its reliability, security and cost.
• Bring AI into how we test where it measurably helps, and show the evidence when it doesn't.

• Define what good looks like for quality engineering at , including for AI-assisted work, and hold that line across teams.
• Lead technically without authority: set standards, review designs and code, and mentor engineers across QA Enablement and the QA chapter.
• Partner with engineering leadership, and with the Engineering Enablement PM, who owns rollout and adoption. You own technical readiness and the evidence that the platform helps.
• A Bachelor's degree in Computer Science, Software Engineering or a related technical field, or equivalent practical experience.
• Typically 10+ years of professional software engineering, including designing and delivering complex systems.
• A track record of setting technical direction across several teams, whatever your title.
• You've built platforms, frameworks or developer tools that other engineers adopted and relied on.
• Deep, hands-on backend and infrastructure engineering: you design, build and run distributed, highly available production systems, and you still write code.
• Expert in at least one backend language, and able to work across others.
• You've built and shipped LLM- or agent-based tools, and can show how you measured whether their output was good enough to trust. You use AI coding tools every day.
• Experience in test infrastructure, developer productivity or CI/CD  don't need a testing background, but you understand what makes tests fast and trusted.
• Clear technical writing: design docs and decisions that other teams act on, and explanations non-technical audiences can follow.

• Building eval infrastructure for LLM or agent output, or testing other non-deterministic systems.
• Giving AI agents the context they need, for example through MCP's and CLI's.
• Moving teams from fragmented tooling onto a shared standard.
• Enough front-end skill to ship usable internal tools.

Our stack includes Java and Python services on GCP and Kubernetes, with Type Script and Playwright for test and UI work.

Experience with them helps, but isn't required.

The years are a guide, not a gate: what you've built and the scope you've owned matter more. If you've done most of this at a comparable level, apply.

At , we believe…