Overview
Security represents one of the most critical priorities for our customers in a world of evolving digital threats, increasing regulatory requirements, growing estate complexity, and rapid advances in AI. Microsoft Security aspires to make the world a safer place by empowering every user, customer, and developer with integrated security solutions that protect across heterogeneous environments. Perception is an advanced Agentic AI platform designed to empower security and IT teams to operate at the speed and scale of AI while adhering to Microsoft’s responsible AI principles. We are looking for a Principal Software Engineering Manager to lead an engineering team responsible for defining, building, and evolving the foundational capabilities of the Perception Platform. This role will focus on enabling AI platform capabilities to operate securely, reliably, and at scale across multiple tenants and diverse enterprise environments. In this role, you will lead engineers solving complex and ambiguous challenges across Generative AI, Retrieval-Augmented Generation (RAG), memory, reasoning, agentic and multi-agent systems, identity and authorization, AI safety, distributed cloud services, and platform infrastructure. You will set technical direction, develop high-performing engineering teams, and drive the delivery of reusable platform capabilities that can support varying tenant configurations, infrastructure dependencies, security boundaries, compliance requirements, and deployment models.
You will lead the strategy and execution for reducing tenant-specific dependencies and creating consistent platform patterns across identity, compute, storage, networking, configuration, deployment, observability, reliability, security, and AI execution. This includes evolving existing production architectures while enabling capabilities to be deployed, configured, validated, monitored, and operated consistently across tenant environments. This role requires proven engineering leadership, deep technical and architectural judgment, and an automation-first mindset, along with demonstrated success building and growing high-performing engineering teams. You will partner closely with engineering leaders, product managers, security experts, architects, and partner teams to translate complex customer, product, security, and tenant requirements into clear engineering strategies, architectures, roadmaps, and execution plans. As a Principal Software Engineering Manager, you will identify systemic engineering challenges, establish technical and organizational direction, develop senior technical talent, and drive architectural alignment across teams. You will create engineering mechanisms and reusable capabilities that extend impact beyond a single feature, service, or team. You will be accountable for both what the team delivers and how effectively it executes, including engineering quality, operational excellence, technical debt management, reliability, security, development velocity, and the growth of engineers and technical leaders. This is an opportunity to lead challenging engineering work at the intersection of AI, security, distributed systems, identity, and multi-tenant cloud architecture, while building the teams and technical foundations needed to deliver Microsoft Security AI capabilities securely and consistently to customers at scale.
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
- Lead, build, and grow a high-performing engineering team responsible for foundational Perception Platform capabilities, fostering an inclusive culture centered on technical excellence, customer impact, accountability, learning, collaboration, and strong engineering ownership.
- Define and drive the engineering strategy, architecture, and execution for production-grade AI platform capabilities spanning generative AI, retrieval and Retrieval-Augmented Generation (RAG), memory, reasoning, model interaction, agent orchestration, execution, evaluation, extensibility, security, and safety. This includes scalable RAG architectures covering ingestion, indexing, embeddings, semantic and hybrid retrieval, context construction, grounding, provenance, re-ranking, retrieval evaluation, and appropriate tenant and authorization boundaries.
- Provide technical leadership for agentic and multi-agent AI systems, including planning, reasoning, tool use, task decomposition and delegation, agent collaboration, state and memory management, human-in-the-loop patterns, failure recovery, and bounded autonomous execution.
- Design scalable, secure, multi-tenant platform architectures with clear engineering principles for tenant isolation, identity boundaries, authentication, authorization, configuration, data protection, deployment, and operations. Drive identity and access patterns across user, workload, service, and agent identities, including Role-Based Access Control (RBAC), delegated authorization, least-privilege access, and secure propagation of identity and authorization context across distributed and agentic workflows.
- Partner with Principal engineers, architects, and senior technical leaders to establish reusable platform abstractions and architectural patterns across compute, storage, networking, identity, configuration, deployment, observability, and service integration. Identify systemic dependencies and evolve existing production services toward reusable, configurable, loosely coupled, and scalable architectures that reduce tenant-specific dependencies and improve engineering leverage across teams.
- Drive an automation-first strategy for platform deployment and operations, including tenant provisioning, configuration, deployment, validation, upgrades, migrations, and operational readiness. Build for differences in tenant configuration, service availability, infrastructure topology, networking, identity, security, sovereignty, and compliance requirements while avoiding unnecessary tenant-specific coupling throughout the application stack.
- Ensure security, authorization, tenant isolation, quality, and reliability are maintained end-to-end across AI retrieval, reasoning, planning, and execution. Establish automated testing and validation mechanisms that verify functional correctness, tenant isolation, authorization, security, configuration, deployment readiness, compatibility, and reliability across heterogeneous environments, including validation of agent-generated plans and tool calls against applicable security, safety, authorization, and compliance policies.
- Own service health, reliability, security, observability, and live-site excellence for the team's platform capabilities. Establish monitoring, diagnostics, and operational practices that enable teams to understand platform health, detect systemic issues, isolate tenant-specific failures, troubleshoot distributed services and AI workflows, prevent incidents, rapidly mitigate issues, perform root cause analysis, learn from failures, and systematically eliminate recurring operational problems.
- Translate long-term technical strategy into clear priorities and execution plans, balancing customer commitments, platform investments, architectural improvements, operational excellence, security, technical debt, and engineering velocity. Use engineering signals, operational metrics, customer feedback, and business priorities to continuously improve platform reliability, engineering productivity, team effectiveness, and customer outcomes.
- Partner across engineering, product, design, security, privacy, compliance, infrastructure, and partner organizations to align dependencies, resolve ambiguity, manage technical risk, and drive complex cross-organizational initiatives to completion. Communicate technical strategy, architectural tradeoffs, risks, priorities, and execution status effectively to engineering teams, partner organizations, and senior leadership.
- Develop and retain strong engineering talent and future technical leaders through recruiting, coaching, mentoring, feedback, delegation, and meaningful growth opportunities. Create an environment where engineers can own complex problems, make high-quality technical decisions, and grow into broader roles.
- Establish and reinforce strong engineering standards and mechanisms across architecture, design reviews, coding quality, security, testing, deployment, operational readiness, and production excellence
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, Go, JavaScript, or Python
- OR equivalent experience.
Other Requirements: Ability to meet Microsoft, customer, and/or government security screening requirements is 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 background and Microsoft Cloud background check upon hire/transfer and every two years thereafter.
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, Go, 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, Go, JavaScript, or Python
- OR equivalent experience.
- Experience leading the design, development, and operation of large-scale multi-tenant distributed systems, cloud services, enterprise platforms, or AI-powered services in production environments.
- Strong architectural judgment and experience partnering with senior and Principal engineers to make complex technical decisions and drive architectural convergence across multiple teams.
- Experience leading systems with strong tenant isolation across identity, authorization, data, compute, configuration, and operational boundaries.
- Experience with Infrastructure as Code, automated provisioning, deployment systems, configuration management, and CI/CD for large-scale cloud services.
- Experience building organizational and technical strategies around reusable abstractions for cloud infrastructure, compute, storage, networking, identity, configuration, and platform dependencies.
- Experience with Kubernetes and containerized service architectures, including deployment, networking, scaling, configuration, capacity management, and operational troubleshooting.
- Experience building and operating highly available and resilient distributed services and designing for dependency failures, capacity constraints, infrastructure differences, and large-scale live-site operations.
- Experience with identity, authentication, authorization, RBAC, least-privilege principles, scoped permissions, delegated authorization, and multi-tenant isolation.
- Experience establishing observability, health monitoring, deployment validation, operational readiness, incident management, and engineering quality mechanisms for large-scale distributed services.
- Experience with Generative AI and AI systems, including model orchestration, retrieval/RAG, semantic search, memory, context management, tool use, evaluation, safety, agentic systems, or production operationalization.
- Experience identifying architectural coupling and leading organizations in evolving existing production systems toward reusable, configurable, and scalable platform architectures.
- Experience managing complex cross-team and cross-organizational engineering programs, including ambiguous requirements, architectural dependencies, competing priorities, and long-term platform investments.
- Strategic technical communication and leadership skills, with experience influencing engineering, product, security, privacy, compliance, infrastructure, and partner organizations.
- Demonstrated ability to balance technical strategy, people leadership, customer impact, operational excellence, and predictable execution while operating in a complex and rapidly evolving environment.
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.