Role at a glance
- Job function
-
AI & Data Generative AI Engineering
- Salary
- $188K – $304.2K/yr
- Location
- Redmond, Washington, United States Atlanta, Georgia, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Education
- Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages...
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Role Summary
The AI Ops Engineering Manager leads an engineering squad building and operating autonomous AI resolution agents for Broad Commercial customers. The role owns engineering execution, production health, evaluation, and business outcomes for AI-driven support capabilities.
What You'll Do
- Hire, develop, and lead engineers building AI-powered solutions while setting technical standards and supporting rapid, reliable innovation.
- Lead end-to-end delivery of autonomous AI systems, including orchestration, retrieval, action execution, and human escalation workflows.
- Define agent architectures, design patterns, evaluation frameworks, reusable platform capabilities, and safe deployment practices.
- Operate the agent fleet by monitoring service health, availability, latency, costs, incidents, and reliability.
- Build evaluation systems and feedback loops using datasets, rubrics, and offline and online evaluation to improve agent quality.
- Turn unresolved cases, customer feedback, and dissatisfaction signals into engineering insights and product fixes.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required: Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in listed languages, or equivalent experience.
Required
- Bachelor's Degree in Computer Science or related technical field and 6+ years technical engineering experience coding in languages...
Preferred
- Master's Degree in Computer Science or a related technical field and 8+ years of technical engineering experience coding in listed...
- Experience building and shipping multi-agent orchestration systems or agentic AI services in production.
- Experience with AI evaluation frameworks, including rubrics, golden datasets, judge agents, and offline and online evaluation.
- Experience with Azure AI Foundry, Azure OpenAI, or comparable enterprise AI platforms.
- Familiarity with agent security patterns, including prompt injection defense, tool access controls, and data boundary enforcement.
- Experience leading co-development or cross-org engineering delivery with multiple partner teams.
- Strong business acumen and ability to tie engineering investment to measurable customer and business outcomes.
- Experience influencing product engineering roadmaps and driving cross-functional collaboration at scale.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Are you a customer-obsessed, AI-curious problem-solver who thrives in an inclusive, collaborative global team? Join Engineering Operations (EngOps), the organization driving operational excellence across the Microsoft Cloud to strengthen quality, reliability, security, and customer trust. Our mission is to prevent issues before they happen by turning operational signals into action through AI-powered automation, enabling measurable customer impact at cloud scale. Our culture of empowerment, inclusion, and growth mindset defines how we work.
Within EngOps ACES, the Agent Fleet Operations (AFO) team is seeking an AI-first Engineering Manager to join Cloud Operational Demand Engineering (CØDE) and help advance our mission of driving operational demand toward zero. We are looking for a technical leader who combines deep engineering expertise with a learn-it-all mindset, is passionate about applying AI to solve real customer problems and is energized by building high-performing teams and systems that scale impact far beyond individual effort.
In this role, you will lead team-building and operating production AI solutions that reduce operational demand and improve customer outcomes. You will be responsible for people leadership, engineering execution, prioritization, and production operations, partnering closely with senior technical leaders to translate strategy into reliable, scalable capabilities. Success requires fostering an inclusive environment where engineers can move quickly, experiment, learn continuously, and deliver high-quality solutions that transform how the Microsoft Cloud operates.
Your Role:
Lead a hands-on AI engineering squad that builds and operates autonomous resolution agents for Broad Commercial customers. You will own engineering execution, production excellence, and business outcomes, not just delivery plans. This role requires a leader who has personally built and shipped production-scale agentic AI systems and can scale that expertise through a high-performing engineering team.
Team charter
Build, operationalize, and scale AI-native support experiences for Broad Commercial customers by transforming supportability knowledge into reusable, versioned, testable, and measurable assets that power product experiences, support engineers, and autonomous agents. The team reduces support demand, engineering toil, and time-to-resolution through AI-driven resolution capabilities that continuously learn from customer signals, unresolved cases, and operational insights.
Responsibilities
Key responsibilities
Build and lead an AI engineering squad
Hire, develop, and lead engineers building AI-powered solutions that reduce support demand, accelerate resolution, and improve customer satisfaction. Set a high technical bar, remain close to architecture and evaluation outcomes, and create the conditions for rapid innovation without compromising quality or reliability.
Own engineering execution for Agentic AI solutions
Own end-to-end delivery of autonomous AI systems, including orchestration, reasoning, retrieval, action execution, and human escalation workflows. Drive capabilities from prototype through production across support surfaces while partnering effectively across dependent engineering organizations.
Set technical direction and engineering standards
Shape the technical foundation for agent development by defining architectures, design patterns, evaluation frameworks, and reusable platform capabilities. Establish standards for prompts, tool interfaces, testing, versioning, code quality, and safe deployment practices to ensure agent behavior remains reliable, observable, and scalable.
Own production health and reliability
Run the service. Own availability, latency, cost per resolution, regression detection, incident response, and the on-call discipline for a fleet of agents acting autonomously in the customer path. Build the observability needed to explain why an agent did what it did, and drive durable fixes rather than repeated mitigations.
Build and maintain evaluation systems
Own the evaluation framework that determines whether agents are safe and effective in production. Build and maintain golden datasets, rubrics, judge agents, and offline/online evaluation pipelines. Use evaluation signals to gate releases and continuously improve quality through production feedback loops.
Drive measurable business impact
Own key business outcomes, including support demand reduction, autonomous resolution rate, resolution quality, time-to-resolution, engineer productivity, and customer satisfaction. Ensure every capability is measurable and that engineering investment is consistently directed toward the highest-impact opportunities.
Transform Customer Signals into Engineering Insight
Create mechanisms that convert unresolved cases, customer feedback, and dissatisfaction signals into actionable engineering insights. Ensure recurring failure patterns improve future agent capabilities and drive product fixes back to the appropriate engineering teams.
Develop Talent and Scale Agentic AI Excellence
Grow engineers into exceptional AI practitioners and extend the team's impact by sharing proven patterns, tools, and operational learnings across the broader organization.
Qualifications
Required qualifications
Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Preferred qualifications
- Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Experience building and shipping multi-agent orchestration systems or agentic AI services in production.
Experience with AI evaluation frameworks: rubrics, golden datasets, judge agents, offline and online evaluation.
Experience with Azure AI Foundry, Azure OpenAI, or comparable enterprise AI platforms.
Familiarity with agent security patterns: prompt injection defense, tool access controls, data boundary enforcement.
Experience leading co-development or cross-org engineering delivery with multiple partner teams.
Strong business acumen, with the ability to tie engineering investment to measurable customer and business outcomes.
Experience influencing product engineering roadmaps and driving cross-functional collaboration at scale.
Background in customer support engineering, supportability, or customer experience platforms.
Experience operating always-on production services, including on-call ownership and incident management.
#EngOps #EngOpsACES
Software Engineering M5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 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.
About the company
Microsoft
Large Enterprise
Microsoft is a global technology leader that empowers individuals and organizations to achieve more through innovative software, services, and devices. Founded in 1975, the company is best known for its flagship products like the Windows operating system and Microsoft Office suite. In addition to personal computing, Microsoft is a leader in cloud computing with its Azure platform, providing a range of solutions for businesses to enhance productivity and efficiency. With a strong commitment to sustainability and accessibility, Microsoft continues to drive technological advancements that shape the future of work and learning.