Job DescriptionThe RoleIn 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 Google Cloud Platform 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 Google Cloud Platform environments.
- Implement robust security in integrations using Google Cloud Platform 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 Google Cloud Platform-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 Google Cloud Platform services such as Cloud Run, Pub/Sub, Cloud Functions, IAM, and API Gateway in event-driven designs.
- Proven ability to integrate bots/agents with enterprise systems (ITSM, HR, CRM, internal APIs) using secure REST/webhook patterns.
- Deep understanding of Google Cloud Platform IAM, OAuth2, service accounts, and enterprise access controls in multi-system integrations.
- Strong proficiency in Python and/or JavaScript frameworks (Node.js, TypeScript) building production-ready backend services and integrations.
- Mastery of core software engineering guardrails, including GitHub-based version control, automated testing, and structured release practices.
- Proven capability to evaluate ambiguous business requests and define clear execution paths (out-of-the-box vs. custom engineering).
- Strong foundational knowledge of corporate identity and access management and corporate data security policies.
- History of delivering clean documentation, handover plans, and operational runbooks alongside deployed code.
- Exceptional communication skills with experience running code reviews, collaborating with TPMs, and leading technical workshops.
What Can Give You a Competitive Advantage (Preferred Qualifications)- Deep experience leveraging Vertex AI Agent Builder, LangChain, or LlamaIndex on Google Cloud Platform to build enterprise-grade, multi-agent systems.
- Proven success migrating legacy enterprise workflows (e.g., Microsoft M365, Power Automate, SharePoint) into native Google Cloud Platform architectures (Cloud Run, Pub/Sub, Vertex AI).
- Experience implementing advanced LLM evaluation frameworks (e.g., Vertex AI AutoSxS, Ragas) and security guardrails (e.g., NeMo Guardrails) for safe production use.
- Practical experience designing complex agentic workflows with HITL validation nodes for highly regulated business processes.
- Track record of building repeatable platform architecture patterns, shared code libraries, and boilerplate templates that enable federated business units to build AI workflows independently.
- Demonstrated success driving cultural and technical adoption of AI tools, including training frameworks and technical enablement workshops.
- Professional Google Cloud certifications such as Professional Cloud Architect, Professional Data Engineer, or Professional Machine Learning Engineer (PMLE).
This job may be eligible for relocation benefits.GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.For a
California-only role, use:
Compensation: The compensation information is a good-faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.
Salary Range: The salary range for this role in California is
$202k-$310k per year. The actual base salary offered will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
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