Engineering Program Manager, Siri AI Performance & Reliability

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.

Were looking for a strong Engineering Program Manager to drive Performance and Reliability for the next generation of Siri, Apples on-device conversational AI. This role sits at the intersection of latency engineering, reliability metrics, and release quality across iOS, macOS, watchOS, tvOS, and visionOS. You will partner with engineering, QE, and data science teams to ensure Siri responds fast, works consistently, and gets measurably better every build. You will coordinate and drive critical projects within the performance and reliability program for Siri AI across active development and release branches. This includes owning the cadence of performance reviews, regression triage, and executive reporting for latency and reliability. Communicate: Provide clear, timely, effective, and objective communication on product latency and reliability KPIs, including regular status to engineering leadership and executive stakeholders. Translate noisy build-over-build data into a coherent narrative about where the product actually stands. Coordinate: Run performance and reliability review forums across component teams and feature areas to identify opportunities for improvement and risks to the performance of the product. Break down complex regressions into actionable discussion topics and drive alignment on ownership. Plan: Own the performance and reliability roadmap against key release milestones. Manage risk for high-visibility use cases, track dependencies across component teams, and re-plan as release health shifts. Execute: Drive resolution of latency and reliability regressions. Establish checkpoints tied to build and release milestones, ensure bugs are filed and owned, and hold teams accountable to the performance bar for each release. Problem solve: Proactively identify regressions, trend reversals, and reliability drops using dashboards, telemetry, and test summaries. Marshal the right engineers, QE, and data scientists to root-cause and resolve, and escalate when critical customer experiences are at risk.5+ years of experience in project or program management. Bachelors or Masters degree in Computer Science, Engineering, or related technical field. Excellent project management skills including structuring programs with multiple interdependent workstreams. Ability to read and reason about data and communicate findings clearly to both engineers and executives. Ability to independently draft and present status, risk assessments, and executive briefings. Strong ability to facilitate technical reviews with senior engineering leaders. Strong leadership skills, including mentoring, team-building, and conflict resolution. Strong verbal and written communication skills, including negotiation, presentation, and influence.3 years driving performance, reliability, or quality programs for large-scale software. Experience with performance programs including requirements and coverage (latency, reliability, telemetry, test infrastructure). Direct experience with performance engineering programs in ML, conversational AI, or on-device inference systems. Familiarity with latency instrumentation, tracing, and profiling concepts. Detailed understanding of build and release processes and regression triage workflows for sophisticated software. Strong analytical thinking, with fluency in dashboards and telemetry tools, and ability to reason over latency distributions, regression trends, build-over-build charts.