Lead AI Workflow Engineer - Enterprise Transformation

The Role As a Lead AI Workflow Engineer – Enterprise Transformation, you will design, build, and scale AI-enabled workflow and automation solutions that modernize how work gets done across General Motors. From the software and core IT side of the transformation, you will focus on eliminating manual effort, simplifying workflows, improving consistency, and enabling business teams to operate effectively across Google Workspace, enterprise platforms, and AI-enabled environments. This role is a strong fit for an experienced engineer who can independently deliver complex workflow solutions, translate business needs into practical technical designs, and build secure, reusable, and supportable automations that align with enterprise standards. You will partner closely with product, engineering, technical program management, security, and business stakeholders to turn high-value manual processes into scalable solutions and to contribute reusable patterns that can be adopted broadly across GM.   What You’ll Do AI workflow engineering and solution delivery Design, build, test, and support AI-enabled workflow and automation solutions across collaboration platforms, enterprise systems, and cloud-native environments. Develop secure backend services, scripts, integrations, and orchestration logic using Python and/or JavaScript frameworks such as Node.js and TypeScript. Build and support event-driven services and workflow components using approved cloud-native patterns and enterprise integration standards. Integrate workflow solutions with enterprise platforms such as IT service management, HR, CRM, document and content platforms, reporting systems, and internal API ecosystems. Translate manual, fragmented, or legacy processes into scalable, supportable, and reusable automation designs. Workflow transformation and business process modernization Partner with business stakeholders, transformation leads, and product teams to understand current-state pain points and identify practical workflow improvement opportunities. Help redesign business processes before automation so teams do not simply recreate inefficient legacy ways of working in new platforms. Support modernization of Microsoft-dependent, spreadsheet-heavy, macro-driven, or manually routed workflows into more durable Google-aligned and cloud-native solutions. Contribute to phased transition and coexistence models where legacy tools or downstream systems must temporarily remain in place during rollout. AI enablement and intelligent orchestration Build and support AI-assisted workflow solutions using approved enterprise AI platforms and orchestration patterns (for example, Gemini-based capabilities and internal AI tools). Implement prompt logic, tool orchestration, exception handling, and validation steps for AI-enabled processes with a strong focus on reliability and supportability. Contribute to human-in-the-loop workflow designs where business or compliance requirements require review, approval, or validation checkpoints. Implement logging, telemetry, and basic evaluation mechanisms to monitor workflow health, agent performance, and operational issues. Technical design, reuse, and standards alignment Evaluate incoming business requests and recommend the appropriate solution path using approved platform capabilities, configuration, low-code/no-code options, or custom engineering. Build reusable services, templates, reference implementations, and accelerators that help teams solve repeatable workflow problems more consistently. Apply enterprise platform standards, approved design patterns, and security requirements in all delivered solutions. Document workflow designs, technical logic, dependencies, integration points, and operational runbooks to support long-term sustainment. Participate in peer reviews, design reviews, and technical discussions to maintain quality, consistency, and supportability. Cross-functional delivery and sustainment Work closely with TPMs,