Principal Technical Program Manager, Developer Productivity

Reddit is a community-driven platform and is seeking a Principal Technical Program Manager for Developer Productivity to lead AI-assisted engineering workflows. This role involves collaborating with engineering leaders to enhance software development processes and ensure effective implementation of AI technologies across the organization.

Responsibilities:

• Partner with Developer Productivity and Infrastructure leaders to translate strategy into executable programs 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 drive the operating model for AI-native developer productivity, including how teams adopt paved paths, how guardrails are applied, how success is measured, and how risks are escalated or resolved
• Create company-level alignment across infrastructure, developer experience, reliability, security, compliance, product engineering, machine learning, and executive stakeholders. You will influence without authority and create clarity across teams with different incentives
• Drive the social and cultural change required for AI-assisted development to succeed company-wide. You will build trust, address skepticism directly, create feedback loops, and help teams move from experimentation to durable adoption
• Develop communication and enablement mechanisms that bring engineers and leaders along for the journey, including leadership forums, working groups, training, documentation, rollout plans, and clear narratives that connect workflow change to business and engineering outcomes
• Build measurement systems that distinguish real productivity from vanity metrics. Partner with engineering and data teams to define industry-aligned 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 adoption in a way that preserves engineering creativity while ensuring security, cost management, privacy, compliance, and operational safety are not afterthoughts
• Use technical judgment to challenge assumptions, identify systemic risks, and guide tradeoffs across AI tooling, CI/CD, code review, deploy automation, developer environments, and production reliability

Requirements:

• 14+ years of experience across technical program management, engineering, infrastructure, developer tools, platform engineering, AI tooling, or related technical domains
• Led multi-year, multi-organization technical programs with executive visibility and ambiguous ownership
• Comfortable operating with senior executives while still understanding the technical details that make or break execution
• 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
• Highly data-driven, but skeptical of shallow metrics
• Exceptional cross-functional operator and communicator
• Led meaningful organizational change, not just program execution
• Get things done; not satisfied with status reporting, process theater, or activity metrics
• Pragmatic and iterative; can introduce structure without making teams feel constrained
• Experience leading developer productivity, platform engineering, infrastructure modernization, or AI tooling programs at large scale
• Experience with LLM platforms, AI-assisted development tools, agentic workflows, or AI governance in an enterprise engineering environment
• Experience building adoption strategies for internal platforms or developer tools where success depends on trust, usability, and measurable value
• Experience leading cultural transformation, change management, or broad adoption programs across 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