Software Engineer III, Mobile Developer Experience

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We're looking for a Mobile Developer Experience Engineer to join PEAS (Productivity Engineering: Automation & Self‑Service) in TechOps. PEAS delivers paved paths, self‑service, and automation‑first developer experiences that help product teams ship quickly and safely. Our scope includes CI/CD platforms, build and test infrastructure, security tooling, and reliability practices: all in service of developer productivity across the org.

This role is the connective tissue between PEAS and the product engineering squads that depend on our platforms, particularly on the mobile side. You'll partner closely with iOS and Android developers to understand their workflows and pain points, then translate those insights into platform improvements, tooling, and automation that make the whole org faster. You should be as comfortable pairing with a mobile engineer on a flaky test investigation as you are designing a reusable CI workflow.

We expect this person to bring an AI‑forward mindset to platform engineering as a practical lens for identifying where intelligent automation, LLM‑powered tooling, and AI‑assisted workflows can meaningfully accelerate developer productivity. You'll help set the direction for how PEAS and the broader engineering org adopt AI in day‑to‑day development.

Reporting to the Manager, Engineering (PEAS), this is a hands-on role with high autonomy, high visibility across the engineering org, and real impact on how quickly product teams can deliver.

What you’ll be doing: 

• Act as a liaison between PEAS and product engineering squads, especially mobile teams: building relationships, gathering feedback, and ensuring platform investments align with real developer needs
• Improve CI/CD pipelines for iOS and Android, with a focus on build times, test reliability, flaky test detection, and fast feedback loops (e.g., Bitrise, GitHub Actions, Datadog CI/Test Visibility)
• Help maintain and evolve shared GitHub Actions and reusable workflows (the "golden path") that give squads well‑lit, low‑friction paths to production
• Identify opportunities to apply AI and intelligent automation to developer workflows (from CI/CD triage and test analysis to code review assistance and self‑service tooling) and drive adoption where the impact is real and measurable
• Contribute to build and test infrastructure (CI runners, simulators, caching strategies) to keep mobile pipelines fast and reliable
• Partner with PEAS teammates on security tooling and reliability practices to ensure pipelines incorporate appropriate guardrails without slowing teams down
• Coach and support engineers on CI/CD best practices, dependency management, effective use of AI‑assisted development tools, and PEAS' shared tooling; create documentation and enablement materials that scale beyond 1:1 conversations
• Champion a data‑driven approach to developer experience: define and track metrics (build times, failure rates, cycle time, developer satisfaction) that guide platform priorities

Qualifications to be successful in this role: 

• 4+ years of relevant work experience
• Substantial experience in software engineering with meaningful time spent in mobile development (iOS and/or Android) or mobile platform/build engineering
• Strong understanding of mobile build systems (Xcode, Gradle), testing frameworks, and the developer workflows around them
• Hands-on experience with CI/CD platforms, particularly GitHub Actions and mobile‑focused CI tools (e.g., Bitrise); comfort building and maintaining reusable workflows at scale
• Demonstrated experience applying AI to real production workflows. Whether that's building LLM‑powered developer tools, integrating AI into CI/CD pipelines (e.g., automated triage, intelligent test selection, AI‑assisted code review), or driving adoption of AI‑assisted development practices across teams
• Excellent communication and cross‑functional collaboration skills. You're the kind of engineer other teams actively want to work with, and you're energized by understanding their problems
• Proficiency in one or more of PEAS' common languages: Go, TypeScript, Python; comfortable contributing to platform code, CLI tools, and automation utilities
• A bias for measurable, automated solutions and a low tolerance