Senior Build Systems & Pipeline Engineer

Adobe Adobe · Enterprise · San Jose, CA

This role focuses on building and scaling the infrastructure for software development and delivery across multiple platforms at Adobe Express. It involves designing and operating high-performance build systems and CI/CD pipelines, with a significant emphasis on integrating and leveraging AI-assisted development workflows and intelligent tooling to improve engineering productivity and efficiency.

What you'd actually do

  1. Architect, implement, and maintain scalable build systems for large multi-platform codebases spanning web, services, iOS, and Android
  2. Design and optimize Bazel-based build infrastructure for performance, reliability, and reproducibility
  3. Build and operate dynamic CI/CD pipelines using platforms such as Buildkite and GitLab
  4. Develop stable and scalable automated test pipelines for web applications, backend services, and mobile platforms
  5. Improve build and test observability through metrics, telemetry, dashboards, alerting, tracing, and pipeline health analysis

Skills

Required

  • BS/MS in Computer Science or equivalent practical experience
  • 6+ years of experience in build systems, CI/CD infrastructure, or developer platform engineering
  • Deep expertise with Bazel build systems in large-scale production environments
  • Strong experience designing and operating dynamic pipelines using platforms such as Buildkite
  • Experience supporting large-scale web and mobile application development environments
  • Strong understanding of build graph optimization, dependency management, caching strategies, and reproducible builds
  • Experience building reliable automated testing infrastructure across frontend, backend, and mobile systems
  • Strong understanding of system observability, metrics, monitoring, telemetry, tracing, and operational health analysis
  • Experience with cloud-native infrastructure and scalable distributed systems
  • Proficiency in one or more programming languages such as Python, Rust, Kotlin, Swift, or TypeScript
  • Strong practical understanding of modern AI-assisted software engineering workflows and tools
  • Experience using AI-assisted development environments such as Cursor, Claude Code, GitHub Copilot, or equivalent tooling in day-to-day engineering workflows
  • Ability to effectively guide, constrain, and evaluate AI-generated output through structured prompting, iteration, validation, and engineering review practices
  • Experience applying AI tooling to workflow automation, debugging, incident analysis, code generation, testing, documentation, or developer experience improvements
  • Understanding of where AI-assisted workflows are effective — and where engineering judgment, validation, and human review remain critical
  • Strong communication and collaboration skills across distributed engineering teams

Nice to have

  • Experience with remote execution environments and distributed build systems
  • Familiarity with monorepo tooling and large-scale source management strategies
  • Experience with release automation and deployment orchestration at scale
  • Experience improving developer experience and internal engineering platforms
  • Experience operationalizing AI-enabled engineering workflows in large engineering organizations
  • Familiarity with agentic developer workflows, multi-step automation systems, or AI- assisted operational tooling
  • Experience designing repositories, documentation, and development conventions optimized for AI-assisted engineering workflows

What the JD emphasized

  • Deep expertise with Bazel build systems in large-scale production environments
  • Strong practical understanding of modern AI-assisted software engineering workflows and tools
  • Experience using AI-assisted development environments such as Cursor, Claude Code, GitHub Copilot, or equivalent tooling in day-to-day engineering workflows
  • Ability to effectively guide, constrain, and evaluate AI-generated output through structured prompting, iteration, validation, and engineering review practices