Job responsibilities
Develop and execute comprehensive program plans (scope, milestones, dependencies, resourcing, timelines) to ensure on-time delivery of ET&P capabilities
Partner with engineering and product to define requirements, success metrics/OKRs, and roadmaps aligned to business and developer outcomes
Identify and mitigate risks; proactively address roadblocks and implement contingency plans to maintain momentum
Drive cross-functional execution across engineering, product, architecture, cybersecurity, and operations to deliver integrated outcomes
Establish and maintain program operating rhythm (intake, prioritization, dependency management, release planning, status reporting, and governance)
Champion adoption of agile ways of working and continuous improvement across teams
Drive programs that deliver and improve CI/CD and release capabilities by partnering with engineering teams; define requirements, manage roadmap/dependencies, and track outcomes
Leverage data-driven insights to improve adoption and productivity (e.g., active usage, DORA metrics, incident trends, lead time)
Uses enterprise-authorized AI capabilities within the work environment to accelerate program planning and risk synthesis (e.g., consolidating inputs into integrated plans, RAID, and executive-ready updates), validating outputs and handling data according to sensitivity requirements
Promotes reuse-first, AI-assisted practices for program governance and reporting, ensuring human review and alignment to delivery standards
Required qualifications, capabilities, and skills
8+ years of experience (or equivalent expertise) in technical program management leading complex technology initiatives in large organizations
Strong stakeholder management skills with ability to influence decisions across engineering, product, and business leaders
Demonstrated ability to independently reason through system behavior, production issues, and reliability/scalability trade-offs with senior engineers
Proven track record managing dependencies, risks, and delivery in fast-paced, agile environments
Strong data-driven approach: ability to define metrics/OKRs, measure impact, and drive continuous improvement
Technical fluency across modern engineering practices (CI/CD, SDLC, release engineering, observability, incident management)
Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support program management workflows with strong validation habits and awareness of data sensitivity
Ability to review and validate AI-assisted plans, risks, and recommendations before use, escalating when uncertain and following data handling expectations
Preferred qualifications, capabilities, and skills
Experience partnering with senior engineering and business leaders to drive adoption of new capabilities and demonstrate measurable outcomes
Experience applying AI/automation to reduce engineering toil and improve delivery efficiency (e.g., test automation, release validation, incident triage, developer self-service)
