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# AI Agent Engineer

- **Company:** General Motors
- **Location:** Austin, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), JavaScript (Programming Language), Microsoft Windows, A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, BASIC (Programming Language), Collaborative Software, Data Structures, Python (Programming Language), Machine Learning, Role-Based Access Control, Microsoft Copilot, Search Technologies, Software Engineering, Systems Integration, TypeScript, User-Centered Design, Data Logging, Enterprise Software Applications, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Generative AI, Agentic-AI, AI Platforms, Information Technology, Virtual Agents, Restful APIs, Semantic Kernel, Serverless Computing, Programming Languages, Microservices
- **Published:** November 6, 2026
- **Apply:** https://www.austinjobsite.com/job.asp?id=3499575893&tx=FL232FFG&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 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, and Data structures, algorithms, and basic ML/LLM concepts.
 * Experience building production services (microservices or serverless) with appropriate observability and testing.

What Will Give You A Competitive Edge (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), and experimentation and A/B testing for AI features.
 * Background in user-centric design or close collaboration with UX teams for AI experiences.

## Description

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.

What You'll Do:

 * 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., This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.