The role is for an engineering leader in the Azure Engineering Operations team, focusing on building and leading a team of Applied AI Engineers. The team aims to enhance Microsoft Cloud customer experiences by improving AI services' quality, security, and reliability. The position emphasizes fostering an inclusive culture and driving measurable business impact through engineering excellence. The leader will also ensure responsible AI practices are embedded in all systems.

• Bachelor's Degree AND 6+ years experience in low-code application development, engineering product/technical program management, data analysis, or product development OR equivalent experience.
• Master's degree in Computer Science, AI, or related field is preferred.
• Experience building and shipping multi-agent orchestration systems or agentic AI services in production.
• Experience with AI evaluation frameworks including rubrics, golden datasets, and judge agents.
• Experience with Azure AI Foundry, Azure OpenAI, or similar enterprise AI platforms.
• Familiarity with agent security patterns such as prompt injection defense and data boundary enforcement.
• Experience leading co-development or cross-org engineering delivery with multiple partner teams.
• Strong business acumen with the ability to tie engineering investments to measurable customer and business outcomes.
• Experience influencing product engineering roadmaps and driving cross-functional collaboration at scale.
• Background in customer support engineering or customer experience platforms is a strong plus.
• 8+ years in software engineering or applied AI roles, with 3+ years in people management leading technical engineering teams.

• Build and lead the AI engineering pod by hiring, coaching, and developing a team of Applied AI Engineers.
• Own engineering execution for agentic AI services, driving the end-to-end lifecycle from spec to deployment.
• Set technical direction and engineering standards for the AI engineering pod, ensuring production-quality code.
• Ensure deployed AI agents meet quality, performance, and safety standards while driving incident response and continuous improvement.
• Build and maintain evaluation systems to validate agent correctness and safety before and after production deployment.
• Influence product and platform roadmaps by partnering with product and Azure service teams.
• Drive measurable business impact by owning KPIs related to automation accuracy and customer satisfaction.
• Ensure responsible AI and compliance by partnering with AI Governance to embed best practices into all agent systems.
• Develop engineering talent by mentoring engineers on applied AI engineering craft and building career growth paths.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.