Principal Corporate Technology Engineer

Microsoft AI•Redmond, WA

3d•$142,800 - $304,200

About The Position

Microsoft AI is seeking a Principal Corporate Technology Engineer to engineer and operate divisional identity, SaaS, access-governance, internal application, integration, and endpoint capabilities. Microsoft AI is an organization of approximately 1,500 people within a larger company. The role helps its endpoints, SaaS products, and distinct services work securely and effectively with centralized identity, security, IT, privacy, compliance, and engineering teams. Initial areas include Slack, Mac operations, other SaaS products, identity governance and administration, and workflow automation. This is not a general end-user support role. The engineer may investigate complex failures and workflows with employees, but the goal is to reduce recurring support through improved systems, secure defaults, automation, documentation, and self-service. The engineer selects appropriate low-code/no-code, scripting, or software-development approaches, ensuring solutions are secure, resilient, maintainable, measurable, and suitable for the operating environment. The role owns divisional corporate technology problems end to end, from discovery and architecture through implementation, deployment, adoption, operations, measurement, and improvement. It maintains an inventory of relevant SaaS, identity, application, and integration assets; strengthens SaaS and identity controls; builds applications and workflows; designs robust integrations; establishes tested delivery and monitoring practices; and partners with Microsoft central teams to deliver supportable outcomes without duplicating centralized capabilities. The team values pace, practical implementations, technical depth, accurate risk communication, and reliable follow-through. Corporate technology is treated as a product and a security-sensitive operating system. The role optimizes for secure employee productivity, builds reusable patterns and documentation, and aims to leave the environment less dependent on any individual.

Requirements

Doctorate in Statistics, Mathematics, Computer Science, or a related field and 3+ years of experience in software development lifecycle, large-scale computing, threat modeling, cybersecurity, anomaly detection, SOC detection, threat analytics, SIEM, IT, or operations incident response; OR master's degree in one of these fields and 4+ years of such experience; OR bachelor's degree in one of these fields and 6+ years of such experience; OR equivalent experience.
Ability to choose suitable low-code/no-code, scripting, or software-development approaches and deliver solutions that are secure, resilient, maintainable, measurable, and appropriate to the operating environment.

Nice To Haves

Doctorate in Statistics, Mathematics, Computer Science, or a related field and 5+ years of experience in software development lifecycle, large-scale computing, threat modeling, cybersecurity, or anomaly detection; OR master's degree in one of these fields and 8+ years of such experience; OR bachelor's degree in one of these fields and 12+ years of such experience; OR equivalent experience.

Responsibilities

Own divisional corporate technology problems from discovery through requirements, architecture, implementation, deployment, adoption, operation, measurement, and continuous improvement.
Maintain an inventory of Microsoft AI-owned or configured SaaS, identity, application, and integration assets; identify risks, ownership gaps, control drift, and recurring operational failures.
Secure and operate the SaaS estate by improving identity integration, SSO and SCIM, administrative roles, guest and external access, OAuth and third-party integrations, data and retention controls, audit logging, service health, and incident readiness.
Engineer identity and access capabilities using Entra and connected systems, including authentication, authorization, conditional access, enterprise applications, application identities, privileged access, joiner-mover-leaver workflows, access packages, access reviews, deprovisioning, and audit evidence.
Build internal applications, automations, integrations, and self-service workflows using appropriate low-code/no-code platforms, APIs, event-driven services, configuration as code, and conventional software engineering.
Design secure, adaptable integration and data layers across SaaS, identity, workflow, endpoint, and business systems, accounting for permissions, secrets, schema and API changes, reconciliation, idempotency, partial failure, retries, auditability, and human escalation.
Establish tested delivery paths, automated validation, telemetry, dashboards, alerting, rollback, runbooks, and service-health measures; detect silent failures and turn recurring issues into durable engineering improvements.
Partner with Microsoft central teams to define service boundaries, clarify decision rights, manage shared dependencies, and deliver outcomes without duplicating central capabilities or creating unsupported technology.
Represent Microsoft AI requirements and constraints to central service owners while preserving supportability, policy alignment, and shared architecture.
Create reusable platforms, patterns, documentation, standards, and mentoring that improve the environment and reduce dependence on the role holder.