Senior Software Development Engineer - Developer Productivity

Adobe•San Jose, CA

About The Position

The Photoshop CI/CD Infrastructure team owns the build, test, and release pipeline that ships one of Adobe's most iconic products across Windows, macOS, iOS, Android and Web. We operate Photoshop's CI/CD pipelines and infrastructure at a significant scale — thousands of builds per day, hundreds of engineers as customers — running across on-premises Apple Macintosh hardware and AWS cloud infrastructure. We are actively evolving our platform to incorporate automation that reduces toil, accelerates developer feedback loops, and allows the group to focus on higher-leverage work. We are building toward an AI Factory model — where intelligent automation handles routine operational decisions and the team focuses on problems that genuinely require human judgment. We are looking for a senior Software Developer to own and advance our CI/CD and AI Factory automation infrastructure. This is a self-directed, high-ownership role built around extensive solution design and end-to-end implementation — you will architect systems from first principles, drive them through design review, and own their delivery and operation in production. A core mandate of this role is to use automation to reduce the reactive support burden on the team. This includes building systems that triage failures, predict flakiness, auto-remediate known issues, and provide insights without human help. You will establish the AI Factory automation patterns and infrastructure that permit the team to prioritize strategic improvements and non-automatable maintenance. As a senior engineer, you will influence across teams, lead technical reviews, mentor peers, and make architectural decisions with lasting impact on how Photoshop engineers build and ship software.

Requirements

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 Haves

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

Responsibilities

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.
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.
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
Architectural decisions for pipeline infrastructure and toolchain evolution across all supported platforms
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
Lead code and design reviews, providing constructive criticism grounded in system-level thinking and production experience
Identify and eliminate toil — proactively find recurring manual work and build automation that removes it permanently, measurably reducing on-call and support burden for the team
Mentor peers on CI/CD best practices, AI-assisted automation patterns, AWS infrastructure, and macOS platform specifics
Cross-team influence — represent the CI/CD team in conversations with platform, security, and product engineering stakeholders; drive AI Factory and cloud infrastructure best practices beyond the Photoshop team to the broader Adobe engineering community