1 day ago
Base Salary
$143k - $304k/yr
Responsibilities
- Lead adoption of AI-native software development practices and Responsible AI controls.
- Own end-to-end architecture for secure, scalable software and data platforms supporting supportability, customer escalation, engineering health, and operational intelligence.
- Lead design reviews and architectural tradeoff decisions for distributed services and data systems.
- Establish standards and guardrails for code quality, testing, observability, deployment safety, and dependency management.
- Architect data models, schemas, lineage, contracts, semantic layers, quality controls, and governance mechanisms.
- Drive telemetry, monitoring, anomaly detection, root-cause workflows, incident prevention, and live-site reliability practices.
- Partner with product, engineering, support, escalation, and leadership stakeholders to create architecture roadmaps and milestones.
- Lead cross-team dependency planning, ownership alignment, and delivery execution.
- Embed secure-by-design, least-privilege, privacy, compliance, and auditability controls into architecture and operations.
- Mentor senior engineers and technical leads and improve architectural quality through reusable patterns.
Requirements
- Bachelor's degree in Computer Science or a related technical field and 6+ years of technical engineering experience with coding in languages including C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including the Microsoft Cloud Background Check.
- Preferred: 10+ years of technical engineering experience, including 5+ years owning architecture for complex, distributed enterprise systems and data platforms.
- Experience delivering large, business-critical initiatives from design through production operations.
- Hands-on backend engineering expertise in coding, testing, debugging, reliability, performance, and maintainability.
- Experience building enterprise AI platforms with AI harnesses, sandbox environments, and reusable capabilities using frameworks such as AutoGen, Semantic Kernel, or LangGraph.
- Experience developing production-grade agentic AI systems operating across distributed systems and generating automated insights.
- Deep data engineering experience including Python/PySpark, ETL/ELT pipelines, data modeling, quality, governance, lineage, and large-scale analytics platforms.
- Expertise in security, privacy, compliance, least-privilege controls, auditability, and secure enterprise deployment.
- Demonstrated ability to align teams, influence technical roadmaps, establish architecture standards, and mentor senior engineers.
Tech Stack
Categories
About Microsoft
Microsoft develops operating systems, productivity software, cloud services, developer tools, and consumer devices for individuals, enterprises, and governments. Its main products include Windows, Microsoft 365, Azure, Visual Studio/GitHub, Xbox, and LinkedIn; revenue comes from software subscriptions and licenses, cloud consumption, hardware sales, and advertising. Founded in 1975 and headquartered in Redmond, Washington, Microsoft is a public company traded on Nasdaq.