About the job
Microsoft Viva Insights (also known as Copilot Analytics) empowers organizations to thrive in the era of AI-powered work. As part of Microsoft 365 Copilot, it delivers privacy-protected, data-driven insights through a unified experience that helps organizations maximize the impact of their workforce by understanding and accelerating the adoption of Copilot and Agents. Our team builds this platform using cutting-edge AI and large-scale data systems to surface actionable insights from collaboration and business signals. We’re hiring a Backend Software Engineer II to help deliver intuitive, AI-powered experiences that enable customers to understand work patterns, optimize collaboration, and realize potential by unlocking the full value of Microsoft Copilot. We also use generative AI extensively in our own development process to move fast, learn continuously, and deliver customer value at scale. In the fast-moving world of AI innovation, we operate with a startup mindset—agile, customer-obsessed, and deeply collaborative. Our inclusive, growth-oriented culture is grounded in Microsoft’s mission to empower every person and organization on the planet to achieve more.
Responsibilities
Design, implement, test, deploy, and operate large‑scale, distributed backend systems that power AI‑driven insights and analytics for Microsoft 365 Copilot and Viva Insights.
Apply generative AI and ML techniques to deliver intelligent, personalized experiences that help customers understand and accelerate their AI transformation.
Act as an embedded engineer for government cloud environments (GCC‑High / DoD), executing onboarding, deployments, troubleshooting, and operational activities with the same ownership and rigor as Core Services full‑time engineers.
Build, manage, and maintain Azure infrastructure across environments, including compute, networking, storage, identity, certificates, and service dependencies, while adapting engineering practices to security‑ and compliance‑constrained environments.
Collaborate across disciplines (product, platform, infrastructure, security, monitoring, compliance) to define technical requirements, design robust APIs, and unblock cross‑service dependencies—particularly in government cloud scenarios.
Drive engineering excellence and service reliability through strong design, testing, observability, proactive monitoring, and deep diagnostics using logs, metrics, telemetry, and Kusto (KQL).
Contribute to team culture by mentoring peers, sharing knowledge, and fostering an inclusive, growth-oriented environment.
Continuously learn and adapt to new technologies, patterns, and best practices in AI, distributed systems, and cloud-native development.
Qualifications
Minimum
Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
3+ years of hands-on software design and coding experience
Experience applying AI/ML techniques or working with generative AI systems in production environments.
Familiarity with modern version control systems like Git and agile development methodologies.
Hands‑on experience with Azure cloud services, including compute, networking, storage, identity, and resource governance.
Experience designing and maintaining infrastructure‑as‑code (e.g., ARM/Bicep or equivalent) and CI/CD pipelines, including YAML‑based build and release definitions, deployment automation, and troubleshooting deployment failures.
Experience supporting live‑site operations, including incident triage, root cause analysis, and driving issues to resolution.
Preferred
Demonstrated experience designing and implementing large-scale distributed systems or cloud platforms.
Solid collaboration and communication skills to work effectively across teams and disciplines.
Prior experience with GCC, GCC‑High, DoD clouds or environments with strict compliance, auditing, or access controls.
Familiarity with EV2 or similar large‑scale deployment orchestration systems.