Agentic AI Engineering Manager for Scalable ML Systems

Google LLC; San Jose, New York (CA, NY); Vor Ort; USD 262.000 - 364.000; Vollzeit

Zusammenfassung

Google LLC in San Jose is seeking an Agentic AI Software Engineering Manager for POps Eng to lead a team building autonomous AI infrastructure. You will define team goals, guide advanced AI research, and drive production-ready systems across Google’s workforce lifecycle.

You will mentor engineers, align product strategy with engineering execution, and ensure scalable, low-latency delivery while managing multi-site teams and budgets.

Qualifikationen

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience managing and developing managers.
• 8 years of experience designing software architecture for applications, including AI/ML systems.
• 8 years of experience building and architecting ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
• 5 years of experience in a people management, supervision/team leadership role.

Aufgaben

• Direct the goal and execution for agentic AI architectures, applying modeling techniques, RL, RM, and classifiers to improve accuracy.
• Lead, grow, and mentor a team of AI/ML software engineers on algorithm design and deployment.
• Bridge applied AI research and production deployment through oversight of tuning, evaluation, and serving infrastructure.
• Improve product excellence and reliability using telemetry and benchmarks across agentic workflows.
• Collaborate with developers, product managers, and internal stakeholders to remove bottlenecks and raise quality.

Kenntnisse

AI architectures

RL/LM methods

People management

Engineering leadership

Ausbildung

Bachelor’s degree or equivalent practical experience

Tools

ML systems infra

RL tooling

Jobbeschreibung

Google LLC in San Jose is seeking an Agentic AI Software Engineering Manager for POps Eng to lead a team building autonomous AI infrastructure. You will define team goals, guide advanced AI research, and drive production-ready systems across Google’s workforce lifecycle.

You will mentor engineers, align product strategy with engineering execution, and ensure scalable, low-latency delivery while managing multi-site teams and budgets.