Manager, Agentic AI Engineering
About The Position
Ingram Micro is seeking a hands-on Manager, Agentic AI Engineering to lead a team of approximately 10 early-career Agent Builders within its AI Center of Excellence (AICOE). The team delivers a portfolio of AI agents, from internal AICOE tools and associate-facing productivity agents to customer-facing solutions. This player-coach role combines team development with delivery of production-grade agents on the AICOE Agentic Platform, applying appropriate rigor based on each agent’s users and risk. AICOE operates a hub-and-spoke model: the hub provides the enterprise Agentic Platform, architecture standards, governance, and AI Ops, while this team and domain teams build and operate agents on the platform. The manager partners with AICOE Platform, Architecture, and AI Ops, as well as business owners across the organization, and reports to the Head of AICOE. The role is based at the Irvine, California corporate headquarters on a hybrid schedule.
Requirements
- Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or a related field.
- 8+ years of software engineering experience.
- 3+ years of engineering management experience leading technical teams.
- Proven experience managing and developing junior or early-career engineers.
- 1–2+ years of hands-on experience shipping GenAI, LLM, or agentic solutions to production.
- Experience evaluating and testing LLM or agent systems, including evaluation sets, regression testing, and quality metrics.
- Strong Python skills and the ability to credibly review code and designs.
- Working knowledge of APIs, distributed systems, vector databases, and RAG architectures.
- Experience with at least one major cloud platform: GCP, AWS, or Azure.
- Strong communication and stakeholder management skills, including communication with non-technical business owners.
Nice To Haves
- Master's degree.
- Proficiency with Google Cloud AI services, including Vertex AI, Gemini models, embeddings, and Agent Engine, and experience running production workloads; equivalent AWS or Azure experience is acceptable.
- Experience with Model Context Protocol (MCP) and agent tool/integration patterns.
- Experience with agent frameworks such as ADK, LangChain/LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar.
- Experience delivering customer-facing AI solutions with associated safety, governance, and compliance requirements.
- Experience with AI observability, guardrails, and production operations.
- Domain experience in sales, customer service, supply chain, logistics, or operational automation.
- Experience leading delivery across multiple concurrent projects in an enterprise environment.
Responsibilities
- Lead, coach, and develop a team of approximately 10 early-career Agent Builders.
- Improve engineering maturity through code reviews, design reviews, pairing, and structured individual growth plans.
- Establish team practices for version control, testing, CI/CD, documentation, and production support.
- Identify and develop future technical leads within the team.
- Own hiring, onboarding, performance management, and career development for the team.
- Foster ownership, curiosity, accountability, and engineering excellence.
- Reduce dependency on individual developers through documentation, reusable components, and shared knowledge.
- Manage a portfolio of agents delivered in parallel, including intake, prioritization, estimation, sprint planning, and status reporting.
- Serve as the primary delivery partner to business owners by clarifying requirements, setting expectations, and communicating progress and trade-offs.
- Guide the design, development, and deployment of agentic and multi-agent solutions, including LLM-powered applications, RAG, tool/MCP integrations, and orchestration.
- Review designs and code, unblock builders, and contribute hands-on when needed.
- Apply AICOE platform and architecture standards and ensure agents meet governance-defined risk-tier, quality, and release requirements.
- Provide delivery feedback to Platform and Architecture teams to help improve standards, reusable components, and tooling.
- Partner with AI Ops to monitor deployed agents for performance, reliability, cost, and user feedback, and drive continuous improvement.
Benefits
- Healthcare benefits
- Paid time off
- Parental leave
- 401(k) plan and company match
- Short-term and long-term disability coverage
- Basic life insurance
- Wellbeing benefits
- Certain roles may be eligible for merit increases, annual bonus or sales incentives, and long-term incentives.
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What This Job Offers
Job Type
Full-time
Career Level
Manager
