Principal Software Engineering Manager

Microsoft • Redmond, WA

2d • $142,800 - $274,800

About The Position

Microsoft Security is seeking a Principal Software Engineering Manager to lead an engineering team responsible for foundational capabilities of Perception, an agentic AI platform for security and IT teams. The role focuses on ensuring AI platform capabilities operate securely, reliably, and at scale across multiple tenants and diverse enterprise environments. The manager will lead work across generative AI, retrieval-augmented generation, memory, reasoning, agentic and multi-agent systems, identity and authorization, AI safety, distributed cloud services, and platform infrastructure.

The role sets technical direction, builds and develops high-performing teams, and delivers reusable platform capabilities that accommodate varying tenant configurations, infrastructure dependencies, security boundaries, compliance requirements, and deployment models. It leads efforts to reduce tenant-specific dependencies and establish consistent patterns across identity, compute, storage, networking, configuration, deployment, observability, reliability, security, and AI execution, while evolving production architectures and enabling consistent deployment, validation, monitoring, and operations across tenant environments.

The manager partners with engineering leaders, product managers, security experts, architects, and partner teams to turn complex requirements into engineering strategies, architectures, roadmaps, and execution plans. The role is accountable for delivery and execution effectiveness, including quality, operational excellence, technical debt, reliability, security, development velocity, and employee growth. It also establishes engineering mechanisms and reusable capabilities that extend impact across teams and services.

Requirements

• Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in languages such as C, C++, C#, Java, Go, JavaScript, or Python, or equivalent experience.
• Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Nice To Haves

• Master's degree in Computer Science or a related technical field and 8+ years of technical engineering experience coding in languages such as C, C++, C#, Java, Go, JavaScript, or Python; or bachelor's degree in a related field and 12+ years of such experience; or equivalent experience.
• Experience leading design, development, and operation of large-scale multi-tenant distributed systems, cloud services, enterprise platforms, or AI-powered production services.
• Strong architectural judgment and experience partnering with senior and principal engineers to make complex technical decisions and drive architectural convergence across 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 developing 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, resilient distributed services designed for dependency failures, capacity constraints, infrastructure differences, and large-scale live-site operations.
• Experience with identity, authentication, authorization, RBAC, least privilege, 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 efforts to evolve production systems toward reusable, configurable, scalable platform architectures.
• Experience managing complex cross-team and cross-organizational engineering programs involving ambiguity, architectural dependencies, competing priorities, and long-term platform investments.
• Strategic technical communication and leadership skills, including 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 in a complex, rapidly evolving environment.

Responsibilities

• Lead, build, and grow a high-performing engineering team, fostering an inclusive culture focused on technical excellence, customer impact, accountability, learning, collaboration, and ownership.
• Define and drive engineering strategy, architecture, and execution for production-grade AI platform capabilities, including generative AI, retrieval and RAG, memory, reasoning, model interaction, agent orchestration and execution, evaluation, extensibility, security, and safety.
• Lead scalable RAG architecture across ingestion, indexing, embeddings, semantic and hybrid retrieval, context construction, grounding, provenance, re-ranking, retrieval evaluation, and tenant and authorization boundaries.
• Provide technical leadership for agentic and multi-agent systems, including planning, reasoning, tool use, task delegation, collaboration, state and memory management, human-in-the-loop patterns, failure recovery, and bounded autonomous execution.
• Design secure, scalable, multi-tenant platform architectures and establish principles for tenant isolation, identity boundaries, authentication, authorization, configuration, data protection, deployment, and operations.
• Drive identity and access patterns for user, workload, service, and agent identities, including RBAC, delegated authorization, least privilege, and secure propagation of identity and authorization context.
• Partner with principal engineers, architects, and senior technical leaders to establish reusable abstractions and architectural patterns across compute, storage, networking, identity, configuration, deployment, observability, and service integration.
• Identify systemic dependencies and evolve production services toward reusable, configurable, loosely coupled, scalable architectures that reduce tenant-specific dependencies.
• Drive automation-first platform deployment and operations, including tenant provisioning, configuration, deployment, validation, upgrades, migrations, and operational readiness.
• Accommodate differences in tenant configuration, service availability, infrastructure topology, networking, identity, security, sovereignty, and compliance without unnecessary tenant-specific coupling.
• Ensure security, authorization, tenant isolation, quality, and reliability end to end across AI retrieval, reasoning, planning, and execution.
• Establish automated testing and validation for 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 policies.
• Own service health, reliability, security, observability, and live-site excellence for the team's platform capabilities.
• Establish monitoring, diagnostics, and operational practices to assess platform health, detect systemic issues, isolate tenant-specific failures, troubleshoot distributed services and AI workflows, prevent and mitigate incidents, perform root-cause analysis, and eliminate recurring problems.
• Translate long-term technical strategy into priorities and execution plans, balancing customer commitments, platform investments, architecture, operations, security, technical debt, and engineering velocity.
• Use engineering signals, operational metrics, customer feedback, and business priorities to improve reliability, productivity, team effectiveness, and customer outcomes.
• Partner across engineering, product, design, security, privacy, compliance, infrastructure, and partner organizations to align dependencies, resolve ambiguity, manage risk, and deliver cross-organizational initiatives.
• Communicate technical strategy, architectural tradeoffs, risks, priorities, and execution status to engineering teams, partner organizations, and senior leadership.
• Develop and retain engineering talent and future technical leaders through recruiting, coaching, mentoring, feedback, delegation, and growth opportunities.
• Establish and reinforce engineering standards and mechanisms for architecture, design reviews, coding quality, security, testing, deployment, operational readiness, and production excellence.

Benefits

• Certain roles may be eligible for benefits and other compensation; additional benefits and pay information is available through the provided Microsoft careers link.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal