Principal Software Engineering Manager

Microsoft•Redmond, WA

13h•$142,800 - $304,200

About The Position

Microsoft Security is developing Perception, an agentic AI platform for security and IT teams. The Principal Software Engineering Manager will lead a team building foundational platform capabilities that operate securely, reliably, and at scale across multiple tenants and diverse enterprise environments. The role sets technical direction and leads delivery across generative AI, retrieval-augmented generation, memory, reasoning, agentic and multi-agent systems, identity and authorization, AI safety, distributed cloud services, and platform infrastructure. It includes reducing tenant-specific dependencies and creating reusable patterns across identity, compute, storage, networking, configuration, deployment, observability, reliability, security, and AI execution. The manager partners with engineering, product, security, architecture, and partner teams to turn complex customer, product, security, and tenant requirements into engineering strategies, architectures, roadmaps, and execution plans. The role is accountable for delivery and engineering effectiveness, including quality, operational excellence, technical debt, reliability, security, development velocity, and the growth of engineers and technical leaders.

Requirements

Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in languages including 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 Background Check and 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 including 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 the 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 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 production systems toward reusable, configurable, and 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 responsible for foundational Perception Platform capabilities, fostering an inclusive culture centered on technical excellence, customer impact, accountability, learning, collaboration, and engineering ownership.
Define and drive engineering strategy, architecture, and execution for production-grade AI platform capabilities spanning generative AI, retrieval and RAG, memory, reasoning, model interaction, agent orchestration and execution, evaluation, extensibility, security, and safety.
Develop scalable RAG architectures covering 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 decomposition and delegation, collaboration, state and memory management, human-in-the-loop patterns, failure recovery, and bounded autonomous execution.
Design scalable, secure, multi-tenant architectures and 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 RBAC, delegated authorization, least-privilege access, and secure propagation of identity and authorization context through distributed and agentic workflows.
Partner with Principal engineers, architects, and senior technical leaders to establish reusable abstractions and 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 and improve engineering leverage.
Drive automation-first 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 while avoiding 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 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 to understand platform health, detect systemic issues, isolate tenant-specific failures, troubleshoot distributed services and AI workflows, prevent and mitigate incidents, perform root cause analysis, learn from failures, and eliminate recurring operational problems.
Translate long-term technical strategy into priorities and execution plans, balancing customer commitments, platform investments, architecture, operational excellence, security, technical debt, and engineering velocity.
Use engineering signals, operational metrics, customer feedback, and business priorities to 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 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 meaningful growth opportunities.
Establish and reinforce engineering standards and mechanisms across architecture, design reviews, coding quality, security, testing, deployment, operational readiness, and production excellence.