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Manager, Agent Engineer, Applied AI

Google
Kirkland, USA
Manager · 8+ years experience
Onsite
USD 262000-364000 / year
Discovered Today
python

Full Job Posting

Responsibilities

  • Serve as the technical lead, establishing code standards, architectural best practices, and benchmarks to elevate development excellence across the team.
  • Partner with sales and tech leadership to define requirements for high-value opportunities, deploying specialized experts (agentic systems in customer experience) to key accounts.
  • Lead technical hiring for Applied AI Agent Development, evaluating AI Agent expertise, systems development, and coding skills to build an exceptional development team.
  • Identify skill gaps in emerging tech (MCP, tool-calling, and foundation models), ensuring the team maintains subject matter expertise in an evolving AI stack.
  • Collaborate with product and development to resolve blockers and translate field insights into roadmaps while building internal tools to drive organizational efficiency.

Minimum qualifications:

  • Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
  • 8 years of experience in cloud computing or a technical customer-facing role.
  • Experience in Python or similar coding languages.
  • Experience developing and deploying agentic solutions utilizing tools, multi-agent workflows and RAG systems.
  • Experience managing customer projects, and in resource management.
  • Experience in a people management, supervision/team leadership role.

Preferred qualifications:

  • Master’s degree or PhD in AI, Computer Science, or related technical fields.
  • 8 years of experience managing software development, agent development, or similar technical customer-facing teams in a cloud computing environment.
  • Experience designing end-to-end secure, observable multi-agent systems using design patterns (ReAct, self-reflection), state management, and tool-calling protocols.
  • Experience designing intuitive interfaces for AI and agentic systems, prioritizing context development, transparency, and explainability to foster user trust.
  • Experience architecting AI solutions within infrastructures, ensuring data sovereignty and secure governance.
  • Experience performing discovery interviews to identify business problems and translate complex hardware/AI constraints for C-suites and technical teams.

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