Drive innovation at Google as an Engineering Manager for People Operations Engineering. This role transcends traditional software engineering, requiring both deep technical expertise and strong leadership acumen. You will guide teams in developing cutting-edge solutions, impacting Google's internal operations and contributing to its mission of making technology more helpful for everyone.

At Corp Eng, we specialize in crafting world-class business solutions that enhance Google's global reach. As the IT backbone for Google, we provide comprehensive support, delivering the essential tools and platforms that empower Googlers to create exceptional products and services.

This is an opportunity to lead significant projects, influence product strategy, and foster the growth of talented engineers.

Lead the architectural vision, design, and successful delivery of advanced AI-powered onboarding agents and integrated hiring workflow platforms.

Cultivate and manage a high-performing team of software engineers in Hyderabad, nurturing both technical excellence and individual career development.

Spearhead the consolidation of outdated recruiting and assessment tools into robust, contemporary enterprise services.

Serve as the primary engineering technical lead for the Hardware and Operations (H and O) team, focusing on the development of sophisticated AI/ML systems and Agentic solutions.

Collaborate closely with Product Management, User Experience (UX), and international engineering leaders to shape roadmaps, define milestones, and articulate technical strategies.

A Bachelor's degree or equivalent practical experience is essential.

Possess a minimum of 8 years in software development, complemented by 3 years of experience in a technical leadership capacity, including project oversight.

Demonstrate 2 years of experience in people management or team leadership.

Proficiency in full-stack web development is required, alongside experience in designing software architecture for applications, specifically incorporating AI/ML systems.

Experience designing and operating large-scale distributed computing systems tailored for AI/ML workloads is crucial.