Senior Engineering Manager, Developer Productivity

23h•$232,500 - $325,500

About The Position

Reddit is seeking a Senior Engineering Manager, Agents & Developer Productivity to lead teams focused on building AI-assisted engineering workflows. This role will collaborate with engineering leaders across various domains, including infrastructure, developer productivity, security, product engineering, ads, and machine learning, as well as senior technical leadership. The primary goal is to ensure that AI-native development at Reddit is safe, measurable, scalable, and effective. The position is crucial as Reddit enters a new phase of software development, leveraging AI and agentic workflows to enhance the speed and confidence of engineers. The manager will be responsible for establishing a flexible yet opinionated framework for agentic development that protects quality, proves value, and fosters trust in new workflows. The Developer Productivity organization is responsible for the platforms, systems, and workflows that enable Reddit engineers to develop, test, review, deploy, and operate software efficiently and safely at scale. This includes working across infrastructure, AI tooling, developer environments, CI/CD, observability, code review, and software delivery systems to reduce friction and improve engineering effectiveness. As AI reshapes software development, this role will be instrumental in defining Reddit's future software development practices, creating foundations for AI-native engineering, including scalable platforms for LLM access and evaluation, safe agent workflows, intelligent development environments, and measurement systems.

Requirements

10+ years of experience across software engineering, engineering management, infrastructure, developer tools, platform engineering, AI tooling, or related technical domains, including experience leading engineering teams.
Managed high-performing engineering teams delivering large-scale technical platforms or infrastructure with executive visibility and cross-functional dependencies.
Deep fluency in developer productivity systems: CI/CD, code review, testing, deployment, observability, developer environments, internal platforms, or AI-assisted development workflows.
Understand AI and LLM-enabled software development beyond personal productivity. Ability to reason about agent workflows, governance, evals, telemetry, code quality, review burden, cost controls, and operational risk.
Highly data-driven, but skeptical of shallow metrics. Know how to build measurement systems that connect workflow improvements to business and engineering outcomes.
Exceptional cross-functional leader and communicator. Ability to bring people together, create clarity across organizations, build trust across functions, and translate complex technical and organizational change into clear narratives for engineers, managers, executives, and cross-functional partners.
Led meaningful organizational change, not just technical delivery. Know how to shift behavior across teams by listening to concerns, building confidence, and making the desired path easier and more valuable than the status quo.
Care deeply about engineering quality, operational excellence, and developer experience, and know how to balance speed with long-term maintainability and reliability.
Pragmatic and iterative. Ability to introduce structure without slowing teams down, and know when a paved path should be adopted through value rather than enforcement.

Nice To Haves

Experience leading developer productivity, platform engineering, infrastructure modernization, or AI tooling teams at large scale.
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.

Responsibilities

Lead and grow high-performing engineering teams focused on AI-native developer productivity, fostering a culture of technical excellence, ownership, inclusion, and continuous improvement.
Partner with Developer Productivity and Infrastructure leaders to 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. 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.

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
Equity in the form of restricted stock units
Commission (depending on the position offered)
Medical, dental, and vision insurance
401(k) program with employer match
Generous time off for vacation
Parental leave