Principal Technical Program Manager - Microsoft Ads (Data, Platform & Tools)

Microsoft•Redmond, WA

8d•$142,800 - $304,200•Hybrid

About The Position

Join Microsoft Ads as a Principal Technical Program Manager and help shape the systems behind ad delivery at global scale. Ads is a demanding and rewarding engineering domain, with high query volume, tight latency requirements, massive compute and data footprints, and a direct path from engineering improvements to measurable customer and business impact. A major initial focus for this role will be ads serving runtime and compute-intensive systems, including GPU/CPU inference performance and efficiency. The role also spans the broader Data, Platform and Tools charter across online and offline ads systems, experimentation, metrics, data platforms and pipelines, capacity, developer tooling, and engineering efficiency. We are looking for a versatile technical leader who can quickly develop depth in critical areas, connect work across the end-to-end ads platform. In this role, you will develop an independent technical point of view grounded in evidence. You will use product requirements, architecture, code paths, production data, logs, experiments, and system behavior to understand complex problems, test hypotheses, identify constraints and trade-offs, and help shape technical direction. You will turn that understanding into end-to-end execution: framing problems, defining outcomes, aligning engineering and product teams, resolving technical and organizational dependencies, driving implementation and launch, measuring impact, and course-correcting when needed. You will partner closely with engineering, product, data science, and business leaders across organizations, while identifying systemic opportunities, shaping technical and program direction across teams, and raising the bar for how complex technical initiatives are structured and executed. Success requires strong technical judgment, curiosity, clear written and verbal communication, ownership, and the ability to earn influence through depth, evidence, and consistent delivery. You are not expected to own every line of production code, but you are expected to understand complex systems end to end, independently find answers, connect decisions across components, challenge assumptions credibly, and drive critical initiatives through to measurable outcomes. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. We build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

Bachelor's Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience.

Nice To Haves

Experience building, operating, optimizing, or troubleshooting high-scale ads serving, recommendation, machine learning, data, experimentation, or other distributed systems.
Understanding of ads technology and how serving, inference, experimentation, data, identity/privacy, and monetization systems work together.
Experience improving the performance, reliability, capacity, or cost efficiency of compute-intensive systems; CPU/GPU inference experience is a plus.
Ability to work hands-on with code, queries, logs, dashboards, experiments, and system documentation to investigate complex behavior and develop an independent technical point of view.
Demonstrated versatility across technical domains and ability to adapt as business and engineering priorities evolve, including effective use of AI tools for technical research, analysis, debugging, and productivity.
Experience driving cross-team change, leading programs with significant customer or business impact, and mentoring TPMs, engineers, or other technical leaders.

Responsibilities

Define and drive the vision, strategy, and measurable outcomes for complex technical programs across the Data, Platform and Tools space.
Drive improvements in performance, reliability, scalability, capacity, cost efficiency, and operational readiness of high-scale production systems.
Develop end-to-end understanding across services and online/offline components by reviewing architecture and code paths, analyzing production data and logs, evaluating experiments, and testing hypotheses.
Form an evidence-based technical point of view, surface trade-offs, and influence engineering and product direction through depth, data, and sound judgment.
Own complex initiatives end to end — from problem framing and solution definition through alignment, execution, rollout, measurement, and course correction — with accountability for outcomes.
Define success criteria, metrics, and guardrails; use experimentation, telemetry, and production signals to assess customer, system, and business impact.
Align engineering, product, data science, and business stakeholders across organizational boundaries, including senior leaders and globally distributed teams.
Identify and resolve technical, organizational, and execution dependencies and risks; navigate ambiguity and obstacles without losing momentum or lowering the quality bar.
Communicate program state early and clearly, including progress, risks, misses, trade-offs, and decisions, to both technical and executive audiences.
Identify systemic opportunities beyond individual initiatives, connect investments across technical areas, and help shape broader technical and program direction.
Use AI effectively for research, analysis, debugging, system understanding, and program execution while applying appropriate technical judgment and validation.
Champion a culture of rigor, curiosity, quality, inclusion, and truth-seeking, with decisions grounded in evidence and systems designed for long-term robustness and scale.