Agentic AI Software Engineering Manager, POps Engineering AI Foundation
Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 13, 2026. Google scores B on the Alion truth index.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
As a Software Engineering Manager in People Operations Engineering (POps Eng), you will lead a team building the autonomous systems and intelligence infrastructure that power the entire Google workforce lifecycle. You will set the technical goal for your team, guiding the application of advanced AI and LLM research to engineer resilient, low-latency production systems. Your leadership will be critical in solving challenges in multi-step reasoning, high-throughput orchestration, and organizational complexity at Google scale.
At Corp Eng, we build world-leading business solutions that scale a more helpful Google for everyone. As Google’s IT organization, we provide end-to-end solutions for organizations across Google. We deliver the right tools, platforms, and experiences for all Googlers as they create more helpful products and services for everyone. In the simplest terms, we are Google for Googlers.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Direct the goal and execution for agentic AI architectures, applying modeling techniques, Reinforcement Learning (RL), Reward Models (RM), and custom classifiers to significantly suppress hallucinations and achieve high-accuracy task execution.
- Lead, grow, and mentor a highly specialized team of experienced AI/ML software engineers working on advanced algorithm design, model tuning (LoRA/SFT), and agentic deployment.
- Bridge applied AI research and production deployment by overseeing engineers driving fine-tuning, reward model alignment, continuous evaluation, and agent serving infrastructure.
- Leverage telemetry, offline/online benchmarks, and developer tooling to improve product excellence, production reliability, and engineering execution velocity across agentic workflows.
- Partner closely with developers, product managers, and internal business owners across Google to identify productivity bottlenecks, coverage gaps, and quality issues.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in 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.
Preferred qualifications:
- 15 years of software engineering management experience building and managing technical engineering teams.
- 5 years of experience applying advanced AI methods, modeling architectures, and alignment strategies to increase accuracy.
- Experience managing software or AI applied research engineers working on fine tuning, modeling, serving, and agentic workflows.
- Experience with reinforcement learning, reward model development, and classifier algorithms.
- Experience presenting technical strategy to cross-functional partners and executive leadership.