Staff SDET

Swap

18h

About The Position

We're looking for a Staff Software Engineer in Test to lead the creation and development of Swap's internal QA Platform — a new function whose mission is to build reusable tools and infrastructure that enable our engineering teams to innovate faster and with confidence. You'll be building the internal platform — tools, frameworks, automation pipelines, and AI-powered workflows — that engineers across Swap use every day to ship safely and fast. Your success is measured by adoption, developer experience, and the speed at which teams can deliver quality software. You will partner with our existing SDET who built the current e2e testing framework, extending its capabilities and building on top of it as part of a broader platform vision. You'll define the strategy, own the roadmap, and make the highest-impact decisions about where to invest the platform's effort.

Requirements

8+ years of experience in software engineering, test engineering, SDET, or platform engineering roles, with significant time spent building developer-facing tools and infrastructure at scale.
Experience building internal platforms, developer tools, or shared infrastructure — you understand what makes engineers actually adopt tooling. You've driven adoption and engagement across multiple teams, not just built features nobody used. This is core to the role.
Strong software engineering fundamentals — you write production-quality code. This role is more engineering than testing.
Deep expertise in test automation frameworks, CI/CD pipeline design, and quality tooling — you've built these systems, not just used them.
Experience with modern cloud infrastructure — Kubernetes, containerised test environments, infrastructure-as-code. You're comfortable with the full stack.
Product thinking for internal tools — you think about your users (engineers), their workflows, and their pain points. You measure success by adoption and impact, not features shipped.
Technical leadership experience — you've led engineering initiatives, defined roadmaps, made architectural decisions, and influenced practices across multiple teams.
Strong communication skills — you can articulate technical vision to engineers and business value to leadership.

Nice To Haves

Experience with AI/LLM-powered testing or developer tools — agentic testing, AI-assisted test generation, or building tooling that integrates LLMs into development workflows.
Experience in e-commerce, fintech, or high-transaction-volume environments where quality has direct business impact.
Experience working across a full engineering organisation — not just one team, but shaping practices and tooling that affect 10+ teams simultaneously.

Responsibilities

Own QA Platform Strategy & Roadmap: Define the vision, strategy, and roadmap for the QA Platform — what to build, in what order, and why. Prioritise ruthlessly for maximum impact. Make high-impact architectural and tooling decisions that shape how quality works across the entire engineering organisation. Track adoption, usage, and developer satisfaction. The platform only succeeds if engineers actually use it — driving adoption and engagement is as important as building the tools.
Build Reusable Quality Tools & Infrastructure: Design and build reusable tools, frameworks, and self-serve quality infrastructure that engineering teams use to ship with confidence — reducing friction to near zero. Partner with the existing SDET to extend and scale the current e2e testing framework into a broader platform with wider capabilities. Create internal developer-facing tools with excellent DX — documentation, clear APIs, easy onboarding. If it's hard to use, it won't be used.
Lead AI-Native Quality Tooling: Build agentic e2e testing capabilities — LLM-driven test generation from user stories and acceptance criteria, running in sandboxed environments. Develop AI-powered workflows for test generation, edge-case fuzzing, visual regression, contract validation, and exploratory testing. Create and maintain a knowledge base of QA best practices, agent skills, MCP servers, and prompt templates that any team can leverage. Continuously evaluate and integrate new AI capabilities as models and tooling improve.
Scale Across the Organisation: Work with every product team to embed quality tooling into their development workflow — making it part of how code is written and shipped, not an afterthought. Onboard teams that currently have no QA coverage into the shared quality ecosystem through self-serve tooling. Build tools that scale independently of QA headcount — the platform should multiply every engineer's ability to ship quality software, not create dependency on the QA team.