Sr. Software Engineer--M365 Foundation Team

Technical Leadership: Serve as a technical lead for a feature crew or major ECS platform area, driving architecture, execution strategy, design quality, and delivery outcomes. Strategic Feature Ownership: Own high-impact ECS capabilities across multiple releases, building roadmaps, evaluating progress, and ensuring investments deliver measurable product, customer, and business value. Complex Problem Solving: Scope and resolve technically complex and ambiguous problems requiring cross-team alignment, architectural judgment, and sustained execution. Agentic-Native Engineering: Lead adoption of AI-assisted and agentic development practices across the crew, including coding agents, MCP-based automation, SKILLs, automated validation, operational intelligence, and modern AI-native engineering practices and evaluation-driven development. Architecture & Design Quality: Develop elegant, resilient, and maintainable designs; improve others' design specs; ensure solutions align with long-term ECS architecture. Reliability & Observability: Define telemetry, health signals, validation strategy, dashboards, and operational readiness criteria for major ECS capabilities. Engineering Lifecycle Improvements: Improve the team's engineering lifecycle, including design reviews, test strategy, CI/CD, incident learnings, release quality, and production readiness. Customer & Partner Engagement: Represent ECS in technical discussions with partner teams and customers, translate pain points into platform improvements, and drive alignment across teams. Mentorship & Culture: Mentor engineers, model strong engineering practices, improve team culture, and help others increase technical depth and execution quality. Risk Management: Identify problems several steps ahead, manage dependencies, make informed tradeoffs, and know when to ship, hold, pivot, or escalate. 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 or equivalent experience. Proven experience leading design and delivery of complex cloud services, distributed systems, or large-scale platform capabilities. Solid proficiency in one or more programming languages such as C#, Java, Python, TypeScript, Go, or Rust. Experience with production service operations, telemetry, reliability engineering, incident analysis, and service quality improvements. Demonstrated ability to lead technical discussions, mentor engineers, and influence decisions across teams. Experience working with AI-assisted development, agentic workflows, automation frameworks, or intelligent engineering tools. 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. Experience with large-scale configuration systems, experimentation platforms, feature rollout, policy enforcement, SDKs, or control-plane infrastructure. Experience leading cross-team initiatives involving service reliability, security, compliance, or platform modernization. Solid understanding of distributed systems design, scalability, fault tolerance, caching, service authentication, and observability. Experience building automation-first operational systems, self-healing workflows, or intelligent troubleshooting experiences. Ability to communicate complex technical issues clearly to engineering leaders, PMs, partner teams, and customers. Demonstrated record of improving engineering practices, driving technical excellence, and developing others. Familiarity with AI-native engineering practices such as harness engineering, loop engineering, evaluation systems, agent orchestration, or automated software development workflows.