Overview

We are looking for a Principal Corporate Technology Engineer to engineer the identity, SaaS, access-governance, internal application, integration, and endpoint capabilities that Microsoft AI operates or configures at the divisional layer.

Microsoft AI is an organization of approximately 1500 people within a much larger company, that values its flexibility to define the workflows appropriate for AI model research – which are not the same as the workflows needed to develop massive enterprise software. As a result, while Microsoft central teams own many important centralized services (like identity), Microsoft AI has a role in making our endpoints, SaaS products and unique services work well and securely in partnership with central identity, security, IT, privacy, compliance, and engineering teams. Initial areas include Slack, Mac operations, and other SaaS products; and their interaction with identity governance and administration and workflow automation.

This is not a general end-user support role. You may work directly with employees to understand difficult failures, test workflows, or resolve high-complexity cases, but success means reducing recurring support through better systems, secure defaults, automation, documentation, and self-service.

Scale and supportability are key parts of this role. Low-code and no-code automations can be helpful, as can scripting or light development work, especially in the age of AI agents (where we have a lot to contribute) – you will be expected to choose the right implementation method for the problem, so long as the result is be secure, resilient, maintainable, measurable, and appropriate for the operating environment.

How We Work

We move with pace and urgency – every week brings new advancements in the frontier, and we don’t want to be blockers. We prefer a useful first implementation over a plan, provided the first implementation doesn’t turn into an albatross over time.

We treat corporate technology as a product and a security-sensitive operating system. We use the services, workflows, and guidance we create. Living with the outcome keeps our work grounded and creates a strong incentive to simplify it, document it, and improve it.

We build credibility through technical depth, accurate risk communication, and reliable follow-through. When a decision is needed, we escalate with evidence, options, and a clear request rather than surprising a partner team.

What You Will Do

Core Responsibilities

Own divisional corporate technology problems from discovery through requirements, architecture, implementation, deployment, adoption, operation, measurement, and continuous improvement.
Maintain a current inventory of the SaaS, identity, application, and integration surface Microsoft AI owns or configures. Use it to find hidden risk, ownership gaps, control drift, and recurring operational failure before they become incidents.
Secure and operate Microsoft AI's SaaS estate. Improve 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. Improve authentication, authorization, conditional access, enterprise applications, application identities, privileged access, joiner-mover-leaver workflows, access packages, reviews, deprovisioning, and audit evidence.
Build internal applications, automations, integrations, and self-service workflows using the appropriate combination of 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. Account for permissions, secrets, schema and API change, 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 operational issues into durable engineering improvements.