Principal Software Engineer Agentic Engineering United States Washington Redmond

Job description

Set the technical vision and multi-year strategy for agentic engineering across WSSI, defining how agents can transform design, implementation, code review, testing, validation, debugging, diagnostics, and release workflows. Lead from architecture through production. Identify the most impactful engineering problems, establish the technical approach, build critical components where needed, and lead focused cross-functional AI squads from experimentation through evaluation, deployment, adoption, and continuous improvement. Pioneer closed-loop agentic engineering systems that combine telemetry, engineering data, tools, and reasoning to detect issues, investigate likely causes, automate diagnostic and debugging workflows, propose and implement solutions, and verify outcomes with appropriate human oversight. Establish the technical architecture for agentic workflows at scale, including reusable approaches for orchestration, context engineering, tool integration, evaluation, observability, reliability, and safe operation in complex engineering environments. Turn technical breakthroughs into organizational momentum. Create the engineering bar for production AI systems. Define rigorous evaluation methods, quality standards, failure-mode analysis, safeguards, and operational practices that enable teams to move from compelling demos to dependable engineering workflows. Measure real engineering impact. Establish outcome measures and feedback loops across engineering productivity, product quality, workflow reliability, developer experience, and sustained adoption, using evidence to guide technical investment and continuously improve deployed systems. Drive technical alignment across organizational boundaries. Build consensus around architecture and engineering standards, influence technical leaders without direct authority, and create durable approaches that teams across WSSI can adopt and extend. Establish rigorous standards for responsible AI, security, privacy, compliance, and human oversight, ensuring agentic systems earn engineers' trust and can be safely integrated into critical engineering workflows. Multiply technical capability across WSSI. Mentor engineers and technical leaders, develop communities of practice, share reusable patterns and lessons, and help teams build the technical proficiency to create and operate agentic workflows independently. Stay ahead of a rapidly evolving field. Maintain deep awareness of relevant industry and research advances, determine which developments matter for WSSI, and translate them into concrete technical recommendations, experiments, and durable engineering improvements. Identify opportunities to expand WSSI's impact. Recognize where technology, architectures, and workflows developed within WSSI can address broader engineering problems, cultivate partnerships around those opportunities, and help shape new areas of technical investment and ownership. Bachelor's Degree in Computer Science, Information Technology, or related field AND 8+ years technical experience in software engineering, network engineering, service engineering, or systems engineering OR equivalent experience. These requirements include but are not limited to the following specialized security screenings: Experience using modern AI-assisted engineering tools and capabilities in software development workflows, including one or more of design, coding, testing, validation, diagnostics, debugging, or operations. Experience leading focused cross-functional teams or AI squads to deliver complex technical initiatives across team or organizational boundaries. Experience moving agentic projects beyond prototypes into production deployment or sustained multi-team adoption, with measurable improvements in productivity, quality, reliability, or developer experience. Experience architecting production agentic systems, including orchestration, tool use, prompt and context engineering, retrieval, evaluation, observability, reliability, cost, latency, and integration into existing engineering environments. Experience delivering telemetry-driven issue detection, validation, automated diagnostics or debugging, code remediation, and closed-loop verification at scale. Experience in one or more of operating system development, driver development, performance and power analysis, responsible AI, security.