Senior Manager, Technical Program Management (Data, Reliability & Developer Experience)

Airbnb

1d•$232,000 - $282,000•Remote

About The Position

Airbnb is looking for a technical, hands-on, and mission-driven Senior Manager of Technical Program Management (TPM) for the Infrastructure TPM team. This role will lead a team of TPMs driving multi-org programs across Data Infrastructure, Reliability Engineering, and Developer Experience. Data Infrastructure focuses on batch, streaming, and real-time data platforms, the semantic metrics layer, and query engines, aiming to make the data stack AI-ready and cost-efficient. Reliability Engineering provides observability, alerting, incident response, and deployment-safety platforms to ensure Airbnb's high availability and resilience. Developer Experience enhances the end-to-end developer workflow, including source control, CI, build, code review, deployment, and cloud development environments, enabling engineers and AI agents to ship quality software quickly and safely. The Senior Manager will collaborate with data, infrastructure, and product teams to develop holistic solutions for a robust, highly available, and transparent platform. They will partner with senior ICs and engineering directors on processes, strategy, and execution, requiring a strong technical background, deep understanding of the problem space, and infrastructure engineering expertise to resolve strategic challenges.

Requirements

12+ years in technical program management, software engineering, or SRE.
5+ years leading and mentoring TPMs or managers of TPMs, creating a culture of inclusiveness and sustainability.
Demonstrated ability to work through ambiguity to detailed solutions.
Strong technical grounding in at least two of: distributed data systems (Spark, Trino, Flink/Kafka, Iceberg), Kubernetes and cloud infrastructure, observability platforms, or CI/CD, build systems, and monorepos.
Track record of leading multi-quarter, multi-team platform migrations or deprecations at scale.
Self-motivated, proactive and proven ability to adapt well and work with teams having different operating cadences.
Sound business judgment, a proven ability to influence others, strong analytical skills, and a track record of taking ownership, leading data driven analyses, and influencing results.
Experience delivering infrastructure for AI workloads or AI-assisted engineering, such as feature platforms, LLM gateways, agentic developer tooling, or scaling CI/CD for AI-generated code.
Deep familiarity with progressive delivery, canary and automated rollback practices, SLOs and error budgets, and incident management.
Excellent written and oral business communication and people skills, with the ability to influence stakeholders.

Responsibilities

Shape and influence the technical direction of projects, ensuring stakeholder needs are met while maintaining high-quality standards.
Drive phased rollouts and large-scale platform migrations, from pilot through adoption to deprecation, with clear exit criteria and minimal disruption to product teams.
Balance broad, outcome-driven thinking with attention to critical details, exercising sound judgment to prioritize where deep focus is necessary to ensure successful execution.
Define and secure stakeholder alignment on clear, measurable success criteria, such as availability and SLOs, CI and merge latency, cost per workload, and adoption, and hold programs accountable to them.
Regularly assess risks and opportunities, and devise proactive mitigation strategies to maintain momentum and project success.
Maintain transparent and effective communication channels to keep stakeholders informed of progress, developments, and challenges.
Expertly present outcomes and updates to senior leadership, clearly and comprehensively articulating trade-offs, risks, and emerging opportunities.
Hire, develop, and coach a team of senior TPMs, and set operating standards for planning, execution, and portfolio reporting across Infrastructure.
Lead programs that prepare infrastructure for AI-driven scale, from CI, source control, and merge systems that absorb higher change volume to agentic developer workflows and AI-ready data platforms.
Partner with engineering and finance on infrastructure efficiency programs, including utilization, cost attribution, and workload-normalized cost reduction.
Drive cross-org reliability programs such as incident review follow-through, SLO adoption, and deployment-safety rollouts.
Own Infrastructure planning rhythms (OKRs, roadmap reviews, dependency mapping) across Data, Reliability, and Developer Experience.