Staff Technical Program Manager, Reliability & Observability

Role Overview

Staff Technical Program Manager (TPM), Reliability & Observability (Infrastructure)

You will join Airbnb’s Infrastructure team to lead Reliability & Observability initiatives. You’ll partner with engineering and product teams to build data-driven decision making across multiple areas, working closely with senior ICs and engineering directors on strategy, processes, and execution.

What You’ll Do

• Shape and influence the technical direction of projects while meeting stakeholder needs and maintaining quality standards.
• Rapidly prototype and validate ideas through iterative development cycles, adapting based on insights and data.
• Balance outcome-driven thinking with attention to critical details to ensure successful execution.
• Define and secure stakeholder alignment on clear, measurable success criteria to accelerate AI initiatives.
• Regularly assess risks and opportunities and devise proactive mitigation strategies.
• Maintain transparent, effective communication with stakeholders on progress, developments, and challenges.
• Present outcomes and updates to senior leadership, clearly articulating trade-offs, risks, and emerging opportunities.

Team/Domain Context

The Reliability & Observability team creates and maintains frameworks and platforms for:

• proactive monitoring and alerting
• logging and tracing
• incident management

This helps teams maintain service health and remediate issues quickly.

Requirements

• 10+ years of work experience, including 8+ years as a TPM or relevant experience.
• Ability to work through ambiguity and turn vague problems into detailed solutions and execution plans.
• Proactive, self-motivated, and able to adapt to teams with different operating cadences.
• Strong business judgment, analytical skills, and proven ability to influence others and take ownership.
• Experience leading data-driven analyses and influencing measurable results.

Nice-to-Haves (from posting)

• Experience with ML models and AI/ML systems, including LLMs/LLMs-like model work, feature development, model testing, and resource management.