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General Motors is seeking an experienced AI Agent Engineer to design and scale enterprise integrations across Serval, SaaS platforms, and GM core systems. You will build secure, reusable pipelines and collaborate with product, security, and business stakeholders to enable reliable data flow and platform interoperability.
You will also craft prompts for large language models, develop templates, guardrails, and validation steps, and help migrate legacy interfaces to modern, API-driven
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. From the software and core IT side of the transformation, 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 a strong fit 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 that align with enterprise standards. 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, while contributing reusable patterns that can be adopted broadly across the enterprise.
Build reusable services, accelerators, and reference integration templates so transformation teams can solve repeatable connectivity needs more consistently. 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 using approved platform capabilities, configuration options, or custom engineering. 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 that support reliable day‑to‑day operations. 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 that improve accuracy, consistency, and reliability. Integrate LLM capabilities with enterprise applications, APIs, data sources, identity services, and downstream systems while addressing security, privacy, latency, and failure‑handing requirements. 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 during phased transformation waves. 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 to reduce operational disruption. 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 into real‑world operational processes. Provide technical leadership through design reviews, implementation guidance, troubleshooting, and engineering best practices across the program. Author technical designs, dependency maps, data mappings, interface specifications, operational runbooks, and handover materials that support long‑term sustainment of integrated solutions. 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.
Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1‑B, OPT, STEM OPT, CPT, TN, J‑1, etc).
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). This job may be eligible for relocation benefits.
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