Jobs · Michigan

AI Agent Engineer

General Motors · Warren, MI · 3 wk ago
HybridFull-time

We are seeking an AI Agent Engineer to design, build, and operationalize AI-powered agents that enhance employee productivity and decision-making in a complex enterprise environment. The ideal candidate combines strong AI/ML foundations, hands-on experience with agent frameworks, and a pragmatic approach to delivering business value in partnership with cross-functional teams. Experience with Glean (or similar enterprise AI search/assistant platforms) is a strong plus.

Responsibilities

  • Design and develop AI agents
    • Engineer and implement AI agents and workflows that automate and augment knowledge work.
    • Translate business requirements into robust agent designs, including tool orchestration, routing logic, and guardrails.
    • Prototype quickly, then harden solutions for reliability, scalability, and maintainability.
  • AI/ML and platform integration
    • Leverage LLMs and related AI services (e.g., retrieval-augmented generation, embeddings, vector search) to power agent capabilities.
    • Integrate agents with enterprise systems, APIs, and data sources (e.g., collaboration tools, knowledge repositories, ticketing systems).
    • Partner with platform teams (e.g., Glean, M365, internal APIs) to ensure secure and compliant integrations.
  • Agent lifecycle management
    • Define and implement monitoring, logging, and feedback loops to continuously improve agent performance.
    • Establish and maintain evaluation frameworks, metrics, and test harnesses for AI agent behavior and output quality.
    • Document agent architectures, decision logic, and dependencies for support and future enhancements.
  • Collaboration and ways of working
    • Collaborate closely with engineers, architects, data teams, and business SMEs in a highly matrixed, global environment.
    • Contribute to shared patterns, reusable components, and best practices for AI agent development.
    • Champion responsible AI, including security, privacy, compliance, and user trust considerations.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, Data Science, or related field; or equivalent practical experience.
  • 3–7+ years of professional software engineering or AI/ML engineering experience in complex, enterprise environments.
  • Strong proficiency in at least one modern programming language (e.g., Python, TypeScript/JavaScript, Java).
  • Hands-on experience with LLM-based applications, AI frameworks, or agent tooling (e.g., LangChain, Semantic Kernel, custom orchestration frameworks).
  • Solid understanding of:
    • Prompt engineering and retrieval-augmented generation (RAG).
    • RESTful APIs and integration patterns.
    • Data structures, algorithms, and basic ML/LLM concepts.
  • Experience building production services (microservices or serverless) with appropriate observability and testing.

Qualifications

Preferred Qualifications:

  • Experience with Glean or similar enterprise AI search/assistant platforms (e.g., integrating sources, configuring tools, designing agents or workflows within the platform).
  • Experience with Microsoft 365 and AI assistants (e.g., Copilot) or other enterprise collaboration ecosystems.
  • Familiarity with:
    • Enterprise identity and access management concepts (e.g., RBAC, least privilege).
    • Observability and telemetry for AI systems (e.g., logging, tracing, quality dashboards).
    • Experimentation and A/B testing for AI features.
  • Background in user-centric design or close collaboration with UX teams for AI experiences.

GM does not provide immigration-related sponsorship for this role. This role is categorized as hybrid, requiring the selected candidate to report to a specific location at least 3 times a week. This job is not eligible for relocation benefits.

Benefits

From day one, we're looking out for your well-being—at work and at home—so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

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