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About the Role

As an AI Agent Engineer, you will design, build, and scale enterprise integrations and data pipelines that modernize how systems work together across General Motors. You will focus on connecting Serval integrations, SaaS platforms, enterprise AI tools, and GM’s core business systems through secure, reusable, and scalable integration patterns. This role is for an experienced engineer who can independently deliver complex integration solutions, translate business and technical requirements into practical system designs, and build supportable, production-ready pipelines. You will partner closely with product, engineering, technical program management, security, and business stakeholders to enable reliable data flow, workflow continuity, and platform interoperability across GM.

Responsibilities

Design, build, and scale enterprise integrations and data pipelines.
Connect Serval integrations, SaaS platforms, enterprise AI tools, and GM’s core business systems.
Build reusable services, accelerators, and reference integration templates.
Apply enterprise platform guardrails by aligning integration designs with data standards, identity guidelines, security policies, and operational requirements.
Partner with Security, Privacy, Identity, Information Lifecycle Management (ILM), and Retention teams to support workflows that process sensitive or regulated data.
Evaluate incoming integration requests and recommend the appropriate technical path.
Define integration architectures that account for system boundaries, data ownership, reliability, observability, failure handling, and long-term sustainment.
Design, build, and maintain robust, resilient, and observable integrations using APIs, webhooks, scripts, connectors, middleware services, and orchestration logic.
Define source-to-destination data mappings, transformation logic, exception-handling patterns, validation rules, and monitoring approaches.
Modernize legacy interfaces, manually routed workflows, platform-specific automations, and older integrations into scalable, API-driven, and event-based integration patterns.
Connect Serval integrations with core GM platforms, including identity services, reporting environments, asset repositories, enterprise applications, and approved AI platforms.
Support end-to-end workflows that move data and trigger actions across enterprise systems.
Troubleshoot integration failures across multi-system environments and improve performance, reliability, and supportability.
Design, test, and refine prompts for large language models used within enterprise workflows and integration solutions.
Develop prompt templates, context strategies, grounding approaches, structured outputs, guardrails, and validation steps.
Integrate LLM capabilities with enterprise applications, APIs, data sources, identity services, and downstream systems.
Support tool calling, workflow orchestration, human-in-the-loop controls, and exception handling for AI-enabled processes.
Apply practical evaluation and monitoring approaches to assess prompt performance, workflow outcomes, and production behavior.
Design and support coexistence models that allow legacy, modern, and internal platforms to interoperate effectively.
Preserve workflow continuity where historical data, inactive-user content, or core systems must remain on legacy platforms during transition.
Support cutover sequencing, permissions validation, metadata mapping, data validation, and post-deployment stabilization.
Identify integration risks and dependencies early and coordinate mitigation across technical and business stakeholders.
Partner directly with transformation Product Leads and Technical Program Managers within business units to integrate Serval capabilities and enterprise platforms.
Provide technical leadership through design reviews, implementation guidance, troubleshooting, and engineering best practices.
Author technical designs, dependency maps, data mappings, interface specifications, operational runbooks, and handover materials.
Support validation, troubleshooting, hypercare, incident resolution, and early-adoption activities during rollout.
Contribute practical feedback that improves integration governance, support models, reusable patterns, and future delivery approaches.

Requirements

7+ years of hands-on experience in integration engineering, systems engineering, software engineering, platform architecture, or enterprise application integration within complex enterprise environments.
Strong systems-thinking capability, with proven experience mapping dependencies across applications, data layers, identity services, integrations, and business processes.
Proven ability to independently lead complex integration initiatives and manage competing priorities across a highly matrixed organization.
Strong production-level proficiency in Python and core scripting or automation frameworks.
Extensive experience building and supporting enterprise-grade integrations using REST APIs, webhooks, middleware solutions, connectors, event-driven services, and ETL or data-transformation logic.
Strong understanding of cloud-based integration patterns, modern application architecture, Git-based version control, structured testing, and debugging integration issues across multi-system environments.
Experience designing secure, supportable integrations across SaaS platforms, enterprise AI tools, Serval integrations, and internal enterprise systems.
Experience with source-to-destination mapping, data transformation, schema management, validation, error handling, monitoring, and operational support.
Extensive hands-on experience prompting large language models for business, technical, or automation use cases.
Experience designing and evaluating prompt templates, context windows, grounding strategies, structured outputs, guardrails, and validation logic.
Experience integrating LLMs with enterprise applications, APIs, tools, data sources, and workflow orchestration components.
Familiarity with tool calling, retrieval-augmented generation, agent or workflow orchestration, human-in-the-loop processes, and LLM observability or evaluation.
Ability to balance AI solution performance with security, privacy, reliability, explainability, cost, and supportability requirements.
Strong foundational knowledge of enterprise authentication, authorization, identity integration, access-control frameworks, and secure API practices.
Experience partnering with Security, Privacy, Identity, ILM, Retention, and compliance stakeholders on integration designs and risk remediation.
Proven history of working effectively with product managers, engineering teams, TPMs, security leads, and business stakeholders.
Strong written and verbal communication skills, including the ability to explain technical tradeoffs, architecture risks, data flows, and engineering decisions to nontechnical partners.
Direct experience supporting Serval integrations or comparable enterprise integration and orchestration platforms.
Experience connecting enterprise workflows to modern data and AI ecosystems, including LLM platforms, enterprise search, automation tools, and data platforms.
Familiarity with corporate data retention, ILM, privacy frameworks, and regulated data controls in large-scale enterprise environments.
Experience supporting automated testing, cutover planning, data validation, hypercare support, and long-term sustainment models.
Experience designing reusable integration frameworks, reference architectures, templates, accelerators, and operational standards.
Familiarity with event-driven architecture, message-based integration, middleware, API management, data pipelines, and cloud-native services.
Experience leading modernization, migration, transformation, or coexistence initiatives involving multiple enterprise platforms.
Relevant cloud, integration, systems engineering, cybersecurity, or AI certifications, or equivalent practical experience.

Skills

Python
REST APIs
Webhooks
Middleware solutions
Connectors
Event-driven services
ETL
Data transformation
Cloud-based integration patterns
Modern application architecture
Git-based version control
Structured testing
Debugging
API integration
SaaS platforms
Enterprise AI tools
Serval integrations
Internal enterprise systems
Source-to-destination mapping
Schema management
Validation
Error handling
Monitoring
Operational support
Large language models (LLMs)
Prompt engineering
Prompt templates
Context strategies
Grounding approaches
Structured outputs
Guardrails
Tool calling
Workflow orchestration
Human-in-the-loop controls
LLM observability
Enterprise authentication
Authorization
Identity integration
Access-control frameworks
Secure API practices
Security
Privacy
Identity
Information Lifecycle Management (ILM)
Retention
Compliance
Product management
Engineering
Technical Program Management (TPM)
Business stakeholders
Written communication
Verbal communication

Location

Hybrid

Work Type

Hybrid

Experience Level

7+ years of hands-on experience
Experienced engineer

Education Level

Bachelor’s degree in Computer Science, Information Technology, Engineering, Information Systems, or a related technical field, or equivalent practical experience.

Benefits

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

About the Company

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.
We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Equal Opportunity

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.
We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities.
Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment.
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.