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Senior Technical Program Manager
United States, Multiple Locations, Multiple Locations
·
On-site
·
Full-time
·
2w ago
Overview:
Are you energized by turning ambiguous, high‑stakes customer problems into crisp, executable technical plans that ship? Do you thrive at the intersection of customers, engineering, and applied science—driving AI solution delivery from use‑case definition through production outcomes?
The Industry Solutions Delivery (ISD) Engineering & Architecture Group (EAG) is a global consulting and engineering organization that supports Microsoft’s most complex and leading‑edge customer engagements. We partner with strategic customers to deliver applied AI capabilities, establish repeatable delivery patterns, and improve how teams build, validate, and operationalize AI solutions at scale.
As a Senior Technical Program Manager, you will be accountable for the “what, how, and when” for customer delivery. On this team, you will serve as the product owner for the engagement, the day‑to‑day customer owner, and a key owner of the technical strategy. You will translate customer problems into a prioritized plan, guide technical direction with engineering and applied science partners, and ensure we ship solutions with measurable business impact.
Responsibilities:
In this role, you will lead end‑to‑end customer delivery across multiple parallel workstreams and use cases. You will deeply understand the customer’s business need, translate it into clear problem statements and success criteria, and define a delivery strategy that balances speed, rigor, and operational readiness. You will run the engagement backlog as the product owner: shaping epics and user stories, prioritizing work, defining validation criteria, and guiding sprint planning and execution so the team can reliably deliver increments of working capability.
You will provide technical program leadership that is hands-on and architecture-aware.
You will partner with engineering and applied science leads to converge on technical approaches, review designs for feasibility and integration risk, and drive decisions on build vs. reuse, experimentation vs. hardening, and performance vs. cost. You will ensure the right instrumentation and evaluation signals exist, telemetry, quality metrics, and end‑to‑end validation, so teams can iterate quickly while maintaining a clear bar for production outcomes.
You will actively own customer alignment and execution with external stakeholders. You will drive workshops and working sessions to clarify requirements, constraints, and dependencies, and you will communicate tradeoffs and decisions with credibility. You will manage stakeholder expectations through crisp, outcome‑based updates, and you will act as the first line of escalation for delivery issues; unblocking teams, driving decisions, and keeping execution on track.
You will own governance, risk, and release readiness for production outcomes.
You will run RAID management and dependency management across teams, anticipate delivery and operational risks early, and implement change control where needed. You will ensure delivery governance meets expectations for quality, compliance, privacy, security, safety, and accessibility as applicable to the engagement. You will drive release readiness end‑to‑end, including staging plans, validation gates, operational readiness checks, go‑live coordination, and post‑release follow‑ups.
Finally, you will scale impact by creating reusable delivery patterns and raising the technical delivery bar across engagements. You will convert learnings into repeatable assets and drive adoption across teams to improve consistency, velocity, and quality over time.
What success looks like (first 6–12 months):
You drive the delivery of novel AI solutions that create clear business impact for customers. You consistently translate ambiguous customer needs into a prioritized backlog and executable delivery plan that ships working outcomes. You run multiple workstreams in parallel with strong technical judgment, predictable delivery mechanics, and clear stakeholder transparency. You raise quality through measurable validation criteria, robust release readiness, and reusable delivery patterns that scale across engagements.
Qualifications:
Required/minimum qualifications
- Bachelor's Degree AND 4+ years experience in engineering, product/technical program management, data analysis, or product developmentOR equivalent experience.
- 2+ years of experience managing cross-functional and/or cross-team projects.
- Demonstrated experience managing cross-functional / cross-team programs with dependencies, risks, and measurable outcomes.
- Hands-on AI/ML technical experience (e.g., implementing prototypes, integrating models or AI services, validating model behavior, defining evaluation signals, or driving operational readiness) sufficient to credibly lead feasibility discussions and execution tradeoffs.
Additional or Preferred Qualifications
- Bachelor's Degree AND 8+ years experience engineering, product/technical program management, data analysis, or product developmentOR equivalent experience.
- 6+ years of experience managing cross-functional and/or cross-team projects.
- 1+ year(s) of experience reading and/or writing code (e.g., sample documentation, product demos).
- Experience delivering AI/ML solutions into production or enterprise environments, including operational readiness and iterative improvement cycles.
- Experience defining success metrics (OKRs/KPIs), using performance data to steer delivery decisions, and driving quality improvements.
- Experience coordinating governance motions and release readiness for customer-facing technical solutions.
- Strong technical communication skills: ability to translate between customer goals, technical constraints, and delivery plans.
Technical Program Management IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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Microsoftについて

Microsoft
PublicMicrosoft Corporation is an American multinational technology conglomerate headquartered in Redmond, Washington.
10,001+
従業員数
Redmond
本社所在地
$3000B
企業価値
レビュー
3.8
5件のレビュー
ワークライフバランス
4.1
報酬
4.3
企業文化
3.4
キャリア
3.2
経営陣
3.0
65%
友人に勧める
良い点
Excellent compensation and benefits package
Four-day workweek with improved work-life balance
Supportive managers and teams
改善点
High-pressure environment causing anxiety
Unprofessional interview processes
Limited creative work opportunities
給与レンジ
5,620件のデータ
Mid/L4
Principal/L7
Senior/L5
Staff/L6
VP
Director
Mid/L4 · Program Manager
0件のレポート
$191,472
年収総額
基本給
$146,773
ストック
$26,238
ボーナス
$18,461
$138,474
$273,204
面接体験
1件の面接
難易度
4.0
/ 5
期間
14-28週間
体験
ポジティブ 0%
普通 0%
ネガティブ 100%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
よくある質問
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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