AI Agent Engineer
General Motors1 day ago
Warren, MI, USA +2 moreSenior
Responsibilities
- Design reusable integration services, accelerators, reference architectures, and templates aligned with enterprise standards.
- Build and maintain resilient integrations and data pipelines using APIs, webhooks, scripts, connectors, middleware, and orchestration logic.
- Define data mappings, transformation and validation logic, exception handling, monitoring, and operational support approaches.
- Connect Serval integrations with identity services, reporting environments, asset repositories, enterprise applications, and approved AI platforms.
- Design and evaluate LLM prompts, context strategies, grounding approaches, structured outputs, guardrails, tool calling, and human-in-the-loop workflows.
- Support legacy modernization, migration, coexistence, cutovers, permissions validation, data validation, hypercare, and stabilization.
- Troubleshoot multi-system integration failures and provide technical leadership, design documentation, runbooks, and implementation guidance.
- Partner with product, engineering, security, privacy, identity, retention, TPM, and business stakeholders.
Requirements
- 7+ years of hands-on experience in integration engineering, systems engineering, software engineering, platform architecture, or enterprise application integration.
- Bachelor’s degree in Computer Science, Information Technology, Engineering, Information Systems, or a related technical field, or equivalent practical experience.
- Production-level proficiency in Python and scripting or automation frameworks.
- Extensive experience with enterprise integrations, REST APIs, webhooks, middleware, connectors, event-driven services, ETL or data transformation, and multi-system debugging.
- Experience with cloud integration patterns, application architecture, Git-based version control, structured testing, data mapping, schema management, validation, monitoring, and operational support.
- Hands-on experience prompting and evaluating large language models and integrating LLMs with applications, APIs, tools, data sources, and workflow orchestration.
- Familiarity with tool calling, retrieval-augmented generation, agent or workflow orchestration, human-in-the-loop processes, and LLM observability or evaluation.
- Knowledge of authentication, authorization, identity integration, access control, secure API practices, privacy, compliance, and regulated data controls.
- Preferred qualifications include Serval or comparable platform experience, reusable integration framework design, cloud or integration certifications, and experience with modernization, migration, testing, cutover planning, and sustainment.
Benefits
- Hybrid work arrangement requiring the selected candidate to report to a specified location at least three times per week, or at a frequency set by the manager.
- May be eligible for relocation benefits.
- GM provides employee benefits and Total Rewards resources from day one.
- GM offers accommodations for applicants with disabilities.
Categories
AI ApplicationsData Engineering
About General Motors
General Motors designs, manufactures, and sells cars, trucks, and electric vehicles for consumers and commercial fleets under brands including Chevrolet, GMC, Cadillac, and Buick. A public company on the NYSE headquartered in Detroit and founded in 1908, it operates globally and is developing EVs on its Ultium battery platform. Revenue comes from vehicle and parts sales, connected services such as OnStar, and financing through GM Financial.