Senior Software Development Engineer - Developer Productivity

Adobe Adobe · Enterprise · San Jose, CA +2

Senior Software Development Engineer to own and advance CI/CD and AI Factory automation infrastructure for Photoshop. This role involves architecting and implementing intelligent automation, integrating LLM capabilities for failure diagnosis, classification, and remediation, and reducing reactive support burden. The engineer will also manage AWS infrastructure, influence architectural decisions, and mentor peers.

What you'd actually do

  1. Build and implement comprehensive solutions by architecting, documenting, reviewing, and delivering complex infrastructure systems end-to-end. Own the full lifecycle from problem definition through production operation, not just individual features or components.
  2. AI Factory automation platform — compose and construct the intelligent automation layer on our continuous integration and delivery environment. Integrate LLM capabilities to auto-diagnose failures, classify root causes, generate remediation suggestions, and surface actionable signals. Replace manual log triage with self-healing pipeline components, including flaky test detection, predictive build health, and automated failure classification.
  3. AWS infrastructure — design and operate cloud-based CI capacity on AWS, including Mac EC2 instances, Auto Scaling groups, EBS volumes, caching, cost optimization strategies, and hybrid on-premises/cloud orchestration
  4. Architectural decisions for pipeline infrastructure and toolchain evolution across all supported platforms
  5. Code standards and patterns for our pipeline tooling codebase (GO Lang, Python, Groovy)— establishing practices that improve consistency and long-term maintainability across the team

Skills

Required

  • 10+ years of software development experience with deep focus on CI/CD, build systems, or developer infrastructure platforms
  • Demonstrated self-direction and solution ownership: a proven track record of designing complex systems from scratch, driving them through review, and delivering them in production — end-to-end
  • Broad solution development experience — comfortable producing architecture documents, leading development reviews, articulating trade-offs, and building consensus across collaborators before writing a line of code
  • AWS — hands-on experience crafting and operating continuous integration and delivery systems on AWS; familiarity with EC2 (including Mac instances), IAM, S3, Auto Scaling, VPC, and cost management
  • AI/ML integration experience — practical experience applying AI tools to automate operational decisions such as failure classification, anomaly detection, or intelligent alerting and self-remediation
  • Proficiency in Python and GO/Shell for production tooling
  • Deep experience with multi-platform build systems (Windows and macOS required; iOS and/or Android a plus)
  • Proven ability to establish norms and models that improve team-wide consistency and reduce recurring issues
  • Experience mentoring engineers and growing technical capability in others
  • Strong debugging instincts across complex, multi-system failures

Nice to have

  • Experience building AI-driven developer tooling — intelligent triage systems, auto-remediation bots, copilots, or similar
  • Familiarity with observability platforms (Splunk, Grafana, CloudWatch, or similar) and using telemetry data to train or prompt AI automation
  • Strong understanding of Xcode, the Apple build toolchain, Universal Binary compilation, code signing and notarization
  • Knowledge of CI/CD security practices — secrets management, infrastructure hardening, threat modeling

What the JD emphasized

  • extensive solution design and end-to-end implementation
  • architect systems from first principles
  • own their delivery and production
  • reduce the reactive support burden
  • build systems that triage failures, predict flakiness, auto-remediate known issues, and provide insights without human help
  • establish the AI Factory automation patterns and infrastructure
  • make architectural decisions with lasting impact
  • 10+ years of software development experience with deep focus on CI/CD, build systems, or developer infrastructure platforms
  • Demonstrated self-direction and solution ownership: a proven track record of designing complex systems from scratch, driving them through review, and delivering them in production — end-to-end
  • Broad solution development experience — comfortable producing architecture documents, leading development reviews, articulating trade-offs, and building consensus across collaborators before writing a line of code
  • AI/ML integration experience — practical experience applying AI tools to automate operational decisions such as failure classification, anomaly detection, or intelligent alerting and self-remediation
  • Proven ability to establish norms and models that improve team-wide consistency and reduce recurring issues

Other signals

  • AI Factory automation platform
  • Integrate LLM capabilities
  • reduce reactive support burden
  • triage failures
  • predict flakiness
  • auto-remediate known issues
  • provide insights without human help
  • AI-assisted automation patterns