Senior Software Engineer

Full Job Description

Lead the design, development, and operation of the platform services and APIs that provision, scale, and secure containerized compute for Agent 365 and Dynamics workloads. Drive architecture and technical strategy for hosting on Azure Container Instances, Service Fabric, and Azure Kubernetes Service, including migrations between hosting models. Own features and components end to end in a DevOps model, from design through deployment, rollout, and live-site support, and break large, ambiguous problems into workstreams the team can execute. Participate in the on-call rotation, drive mitigation of live site production incidents, and own root cause analysis and post-incident reviews through to repair items. Use telemetry, logging, and monitoring to drive data-informed decisions on reliability, performance, capacity, and infrastructure cost. Partner with peer teams across Dynamics 365, Power Platform, and Copilot to align on platform requirements, feature development, and onboarding new scenarios. Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Deep hands-on experience with container technologies such as Docker and Kubernetes, and with Azure compute services such as AKS, Azure Container Instances, Service Fabric, or Virtual Machine Scale Sets. Experience with infrastructure as code, CI/CD, and safe deployment practices (for example ARM or Bicep templates and Azure DevOps pipelines). Experience with Azure networking concepts including virtual networks, DNS, and load balancing. Experience with large-scale observability and diagnostics tooling, such as distributed tracing, metrics, and log analytics. Experience with generative AI, agentic workloads, or LLM/ML systems, and an interest in the infrastructure problems they create.

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