AI Agent Engineer

General Motors (GM)

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Warren, MIAustin, TX
Employment
Full-time
Posted
95 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $196k
$140k $246k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $157,025–$235,750.

Based on 240 similar postings.

Employer

About General Motors (GM)

General Motors (GM) is a leading American multinational automotive corporation founded in 1908 and headquartered in Detroit, Michigan.

General Motors (GM) currently has 196 open roles on FindRole.

Listed pay typically runs $159,200–$245,000 across 54 roles with salary data.

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At a glance

TL;DR · AI Agent Engineer

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The AI Agent Engineer will join a team to design, build, and operationalize AI-powered agents that enhance employee productivity and decision-making within a complex enterprise environment. The role involves translating business requirements into robust agent designs, implementing workflows that automate knowledge work, and managing the full agent lifecycle including monitoring, logging, and evaluation. You will leverage LLMs, retrieval-augmented generation, embeddings, and vector search to power capabilities while integrating with enterprise systems, APIs, and data sources like M365. Required skills include proficiency in Python, TypeScript/JavaScript, or Java, along with experience in LangChain, Semantic Kernel, and prompt engineering. You will solve technical challenges related to tool orchestration, routing logic, and guardrails while ensuring secure, compliant integrations and maintaining production services using microservices or serverless architectures.

Skills

Python TypeScript JavaScript Java LangChain Semantic Kernel LLMs RAG Vector Search RESTful APIs Microservices Serverless Prompt Engineering Microsoft 365 Glean Observability RBAC

What you'll do

  • Design and implement AI agents and workflows to automate and augment knowledge work.
  • Translate business requirements into agent designs featuring tool orchestration, routing logic, and guardrails.
  • Leverage LLMs and AI services like RAG, embeddings, and vector search to power agent capabilities.
  • Integrate agents with enterprise systems, APIs, and data sources like collaboration tools and ticketing systems.
  • Define and implement monitoring, logging, and feedback loops to improve agent performance.
  • Establish 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.
  • Champion responsible AI practices including security, privacy, compliance, and user trust considerations.

What we're looking for

  • Bachelor’s degree in Computer Science, Engineering, Data Science, or a 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 such as Python, TypeScript/JavaScript, or Java.
  • Hands-on experience with LLM-based applications, AI frameworks, or agent tooling like LangChain or Semantic Kernel.
  • Solid understanding of prompt engineering, retrieval-augmented generation (RAG), RESTful APIs, and data structures.
  • Experience building production services like microservices or serverless with appropriate observability and testing.
  • Experience with Glean or similar enterprise AI search/assistant platforms (preferred).
  • Experience with Microsoft 365, AI assistants, or enterprise identity and access management concepts (preferred).

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