Director of Engineering, Developer Productivity

The Developer Productivity organization builds the platforms, systems, and workflows that enable Reddit engineers to develop, test, review, deploy, and operate software safely and efficiently at scale. We work across infrastructure, AI tooling, developer environments, CI/CD, observability, code review, and software delivery systems to reduce friction, improve engineering effectiveness, and help teams focus on delivering impact for Reddit users.

Responsibilities

• Lead teams across Reddit's Developer Productivity and AI portfolio, spanning agent infrastructure, AI-assisted code review, developer environments, LLM governance, developer tooling, AI workflow measurement, and software delivery automation.
• Partner deeply with engineering teams as a technical leader, balancing execution, organizational alignment, technical quality, and long-term platform strategy.
• Translate strategy into scalable platforms and engineering roadmaps across code review, agent infrastructure, self-service LLM access, evaluation and observability systems, development environments, and safe agent workflows across the software development lifecycle.
• Define and evolve the operating model for AI-native software development, including paved paths, platform adoption strategies, governance models, and engineering standards that enable safe and effective experimentation at scale.
• Drive alignment across infrastructure, developer experience, reliability, security, compliance, product engineering, machine learning, and executive stakeholders.
• Build engineering systems and organizational processes that help teams move from experimentation to durable adoption of AI-assisted workflows while maintaining quality, reliability, and operational safety.
• Develop communication and enablement mechanisms that bring engineers and leaders along for the journey, including technical strategy reviews, working groups, training, documentation, rollout plans, and clear narratives that connect workflow change to business and engineering outcomes.
• Build and operationalize measurement systems that distinguish real productivity from vanity metrics. Define metrics such as design-to-test time, test-to-launch time, review turnaround, change failure rate, time to restore service, AI-authored code quality, AI-assisted pull request load, migration throughput, and developer satisfaction.
• Partner with engineering and data teams to define metrics such as design-to-test time, test-to-launch time, review turnaround, change failure rate, time to restore service, AI-authored code quality, AI-assisted pull request load, migration throughput, and developer satisfaction.
• Drive AI governance and platform adoption in a way that preserves engineering creativity while ensuring security, cost management, privacy, compliance, and operational safety are built into the development lifecycle.
• Use technical judgment to challenge assumptions, identify systemic risks, guide architectural tradeoffs, and help teams make pragmatic decisions across AI tooling, CI/CD, code review, deploy automation, developer environments, and production reliability.
• Partner with senior engineering leadership on organizational planning, technical investment strategy, hiring, career development, and long-term platform evolution.

Qualifications

• 14+ years of experience across software engineering, engineering management, infrastructure, developer tools, platform engineering, AI tooling, or related technical domains, including experience leading engineering teams.
• Deep fluency in developer productivity systems: CI/CD, code review, testing, deployment, observability, developer environments, internal platforms, or AI-assisted development workflows.
• Experience with LLM platforms, AI-assisted development tools, agentic workflows, or AI governance in an enterprise engineering environment.
• Experience building internal platforms or developer tools where success depends on trust, usability, reliability, and measurable value.
• Experience leading organizational transformation, platform adoption, or engineering workflow modernization initiatives across large engineering organizations.
• Familiarity with engineering productivity frameworks such as DORA, SPACE, or similar multi-dimensional measurement approaches.
• Experience working in fast-moving environments where technical strategy, organizational design, and execution mechanisms are evolving at the same time.

Benefits

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave
• Pay Transparency