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Software Engineering Manager, Business AI Agent

Google
California, USA
Manager · 8+ years experience
Onsite
USD 207000-300000 / year
Discovered 1 weeks ago
javapython

Full Job Posting

Responsibilities

  • Manage and mentor a Software Engineering team, owning the roadmap and architecture for applied AI, low-latency scoring, and automated evaluation.
  • Lead Knowledge Library and merchant control engineering, building advanced RAG integrations (PDF ingestion, auto-learning) for custom agent behavior.
  • Oversee autonomous execution tooling and Universal Commerce Protocol (UCP) integration to enable active user journeys (catalog lookups, universal carts, reservations).
  • Advocate prompt tuning and loss diagnosis while scaling LLM-based AutoRater frameworks to reduce hallucinations and measure conversation factuality.
  • Partner with Product, Data Science, UX, and core Google platform teams to define Ground Truth datasets, investigative dashboards, and model upgrade standards.

Minimum qualifications:

  • Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
  • 8 years of experience coding in one or more general-purpose programming languages (e.g., Python, Java, C++, or Go) focused on backend system architecture.
  • Experience building automated LLM evaluation pipelines, automated rating systems (AutoRaters), or defining LLM-specific reliability metrics (e.g., measuring grounding, helpfulness, safety, and hallucination/error reduction).
  • Experience with backend, distributed systems, or AI/ML systems infrastructure.
  • Experience managing software engineers, including performance management, mentoring, and team growth.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical field.
  • 3 years of experience working in a complex, matrixed organization.
  • Experience developing, calibrating, and productionizing LLM-based AutoRater frameworks or automated regression testing.
  • Experience designing agentic tooling and integrating agents with commerce platforms.
  • Experience in conversational AI architectures, agent orchestration harnesses, and retrieval-augmented generation (RAG) for knowledge libraries.
  • Track record of technical leadership partnering with Product Management, Data Science, and UX to build "Ground Truth" datasets and performance-tracking dashboards.

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