Job description

Overview MCAPS-Core accelerates customer outcomes and business growth. By uniting product, engineering, marketing, sales, customer success, and partners around a common customer mission, we help customers realize value faster and turn innovation into measurable business impact. Through deep technical expertise and differentiated go-to-market execution, we win competitively, capture market share, and scale repeatable growth motions. We differentiate through value creation - delivering world-class, AI-powered customer experiences that accelerate adoption, strengthen loyalty, and create sustainable competitive advantage, driving growth that outpaces the market. Within MCAPS - Core, the Customer Service & Support (CSS) organization builds trust and confidence for every person and organization through delivering a seamless support experience. In CSS, we are powered by Microsoft’s AI technology to help consumers, businesses, partners, and more, resolve their issues quickly and securely, helping prevent future problems from occurring and achieving more from their Microsoft investment. Microsoft’s SCIM organization is seeking a Principal Software AI Engineer to lead the architecture, development, and production deployment of agentic AI solutions that transform support experiences. This is a hands-on technical leadership role for an engineer who can solve ambiguous, high-impact problems; set engineering direction; and translate support experience intent and readiness requirements into secure, reliable, and scalable AI systems. You will combine deep software engineering expertise with applied AI judgment to build diagnostics, workflows, evaluation frameworks, and tooling that improve how support teams and customers resolve complex issues. You will work across engineering, product, program management, data, security, Responsible AI, and frontline support teams, influencing technical strategy while remaining close to implementation. This role is suited to a principal-level engineer who combines strategic influence with deep hands-on execution. The ideal candidate is energized by ambiguous problems, makes sound architectural tradeoffs, learns rapidly as AI technologies evolve, and maintains a high bar for customer impact and operational excellence. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Responsibilities • Architect and build production-grade AI systems. Design, implement, and operate agentic AI solutions, diagnostic experiences, orchestration workflows, and supporting platforms using governed ProCode and citizen-development technologies where appropriate. • Set technical direction. Define architecture, engineering strategy, design principles, and reusable patterns for AI solutions that must operate securely and reliably at enterprise scale. • Lead through code and engineering rigor. Develop critical components, conduct design and code reviews, establish testing standards, and resolve the most complex technical and architectural issues. • Integrate with the support ecosystem. Connect AI solutions to Microsoft support systems, APIs, knowledge sources, telemetry, and enterprise data while ensuring appropriate access controls and data handling. • Advance agent orchestration and diagnostics. Solve difficult problems in planning, context and state management, tool use, multi-agent coordination, retrieval, grounding, observability, and failure recovery. • Build robust evaluation capabilities. Establish technical, unit, integration, regression, and end-to-end testing for prompts, models, tools, orchestration flows, and system integrations. • Validate quality and readiness. Evaluate groundedness, accuracy, task completion, robustness, latency, cost, safety, and failure modes at each deployment milestone in partnership with TPMs and support-domain experts. • Deliver enterprise-ready solutions. Deploy and operate services in Microsoft cloud environments in accordance with security, privacy, compliance, Responsible AI, reliability, and scalability requirements. • Define measurable outcomes. Establish success metrics and telemetry that demonstrate customer value, support effectiveness, engineering health, operational readiness, and suitability for scale. • Drive operational excellence. Create monitoring, incident response, debugging, and continuous-improvement mechanisms for AI systems in production. • Influence across organizations. Partner with senior leaders and cross-functional teams to align priorities, manage technical tradeoffs, and deliver strategic initiatives spanning multiple organizations. • Grow engineering capability. Mentor engineers, raise the technical bar, promote thoughtful experimentation, and build a culture of inclusive collaboration, knowledge sharing, and high-quality execution. • Document for long-term success. Maintain clear architecture, design decisions, limitations, evaluation evidence, deployment guidance, and operational runbooks. Qualifications Required/minimum 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 Other Qualifications • Microsoft is unable to sponsor a work visa for this role due to the nature of the role’s job duties. • Ability to meet Microsoft, customer and / or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire / transfer and every two years thereafter. Additional or 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. • Hands-on experience building applied AI systems, including generative AI, large language models, or autonomous agents. • 10+ years of professional software design and development experience, including architecture and delivery of complex production systems. • Experience designing, building, deploying, and operating highly available, secure, and scalable cloud services • Strong proficiency in one or more modern programming languages, with the ability to contribute directly to production code; experience with Python is highly relevant. • Experience with distributed systems, APIs, data platforms, observability, testing, and production operations. • Strong communication skills and the ability to explain complex technical decisions to engineering, product, business, and executive audiences. • Experience with Azure AI Foundry, Copilot Studio, Power Platform, Azure services, or comparable enterprise AI and cloud platforms. • Deep expertise in one or more of the following: agent platforms, multi-agent orchestration, retrieval-augmented generation, knowledge systems, AI evaluation, prompt engineering, model selection, or ML infrastructure. • Exerience developing evaluation frameworks and quality gates for generative AI, including groundedness, safety, robustness, and task-success measurement. • Experience integrating AI solutions with enterprise systems, security boundaries, identity, data governance, and compliance controls. • Experience building AI-powered diagnostics, customer support, service operations, or workflow automation solutions. Software Engineering IC5 - 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: careers.microsoft.com 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.

Requirements

Must-haves

Set technical direction. Define architecture, engineering strategy, design principles, and reusable patterns for AI solutions that must operate securely and reliably at enterprise scale.
Lead through code and engineering rigor. Develop critical components, conduct design and code reviews, establish testing standards, and resolve the most complex technical and architectural issues.
Integrate with the support ecosystem. Connect AI solutions to Microsoft support systems, APIs, knowledge sources, telemetry, and enterprise data while ensuring appropriate access controls and data handling.
Advance agent orchestration and diagnostics. Solve difficult problems in planning, context and state management, tool use, multi-agent coordination, retrieval, grounding, observability, and failure recovery.
Build robust evaluation capabilities. Establish technical, unit, integration, regression, and end-to-end testing for prompts, models, tools, orchestration flows, and system integrations.
Validate quality and readiness. Evaluate groundedness, accuracy, task completion, robustness, latency, cost, safety, and failure modes at each deployment milestone in partnership with TPMs and support-domain experts.
Deliver enterprise-ready solutions. Deploy and operate services in Microsoft cloud environments in accordance with security, privacy, compliance, Responsible AI, reliability, and scalability requirements.
Define measurable outcomes. Establish success metrics and telemetry that demonstrate customer value, support effectiveness, engineering health, operational readiness, and suitability for scale.
Drive operational excellence. Create monitoring, incident response, debugging, and continuous-improvement mechanisms for AI systems in production.
Influence across organizations. Partner with senior leaders and cross-functional teams to align priorities, manage technical tradeoffs, and deliver strategic initiatives spanning multiple organizations.
Grow engineering capability. Mentor engineers, raise the technical bar, promote thoughtful experimentation, and build a culture of inclusive collaboration, knowledge sharing, and high-quality execution.
Document for long-term success. Maintain clear architecture, design decisions, limitations, evaluation evidence, deployment guidance, and operational runbooks.
Required/minimum qualifications
Other Qualifications
Microsoft is unable to sponsor a work visa for this role due to the nature of the role’s job duties.
Hands-on experience building applied AI systems, including generative AI, large language models, or autonomous agents.
10+ years of professional software design and development experience, including architecture and delivery of complex production systems.
Experience designing, building, deploying, and operating highly available, secure, and scalable cloud services
Strong proficiency in one or more modern programming languages, with the ability to contribute directly to production code; experience with Python is highly relevant.
Experience with distributed systems, APIs, data platforms, observability, testing, and production operations.
Strong communication skills and the ability to explain complex technical decisions to engineering, product, business, and executive audiences.
Experience with Azure AI Foundry, Copilot Studio, Power Platform, Azure services, or comparable enterprise AI and cloud platforms.
Deep expertise in one or more of the following: agent platforms, multi-agent orchestration, retrieval-augmented generation, knowledge systems, AI evaluation, prompt engineering, model selection, or ML infrastructure.

Nice-to-haves

Additional or preferred qualifications

Application prep

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