Senior AI Workflow Engineer - Enterprise Transformation

The Role In this role, you will own the end-to-end transformation of business workflows using AI. Rather than just building prompts or standalone agents, you will design secure, reusable, enterprise-grade AI solutions that modernize how work gets done across GM. You will partner closely with engineering, product, and business teams to define platform standards, shape architecture, and scale AI adoption, from intake and solution design through governance and long-term sustainment. You will also work directly with business teams to identify high-value workflow transformation opportunities and drive consistent AI patterns across both collaboration and enterprise AI platforms. What You’ll Do Write clean, scalable, and secure backend services and integrations using Python and/or JavaScript frameworks (Node.js, TypeScript). Build and operate cloud-native, event-driven services on GCP using Cloud Run, Pub/Sub, Cloud Functions, and API Gateway. Code data pipelines and integration layers to migrate legacy enterprise workflows (e.g., M365) into native GCP environments. Implement robust security in integrations using GCP IAM, OAuth2, service accounts, and enterprise access controls. Build and maintain automated testing frameworks, CI/CD pipelines (GitHub), and structured release environments. Engineer and deploy production-grade multi-step AI agents and bot-driven workflows integrated with Vertex AI, Gemini, and external LLMs. Architect and code Human-in-the-Loop (HITL) validation nodes into automated pipelines for critical business processes. Design, test, and optimize production prompts and agent instructions with guardrails, exception handling, and failure-recovery logic. Implement telemetry, structured logging, and evaluation frameworks to monitor agent performance, accuracy, and latency. Evaluate ambiguous business requests and author technical designs that translate them into clear execution pathways. Own technical intake decisions: recommend when to use platform capabilities, configuration, or custom AI solutions. Create reusable architecture patterns, code templates, and shared libraries that enable internal developers to scale AI workflows. Deliver comprehensive technical documentation, API specifications, blueprint repositories, and operational runbooks with all deployed code. Lead rigorous code reviews for peer engineering levels to maintain code quality, security, and architectural alignment. Your Skills & Abilities (Required Qualifications) 10+ years of hands-on experience in software engineering, platform architecture, or enterprise workflow automation in complex, highly matrixed corporate environments. Proven experience leading or contributing to GCP-based transformations, including cloud migration, modernization of enterprise workloads, and adoption of scalable, secure, AI-enabled solutions. Strong track record navigating large-scale technology transformations, including tenant-to-tenant migrations and platform shifts (e.g., migrating workflows out of Microsoft M365). Demonstrated success modernizing legacy or manual workflows into API-driven, event-based, or agent-assisted applications. Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field, or equivalent practical experience. Experience designing and deploying AI agents or bot-driven workflows using frameworks integrated with Vertex AI, Gemini, or external LLMs. Deep understanding of multi-step workflow orchestration, including tool use, state handling, and integration across enterprise services. Practical experience building reliable, production-grade prompts and agent instructions with strong guardrails and failure handling. Demonstrated experience implementing telemetry, logging, and evaluation frameworks for production AI agents. Strong hands-on experience with GCP services such as Cloud Run, Pub/Sub, Cloud Functions, IAM, and API Gateway in event-driven designs. Proven ability to