Senior AI Software Engineer - (Enterprise Transformation)
for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Use - for any list of duties/requirements/benefits, and
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate, navigation, legal, EEO, equal-opportunity, scam-warning, duplicated lines, application instructions. Preserve all substantive information; do not invent or summarize away detail. Include a section ONLY when posting has real, specific content for it—never emit heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless posting actually states them. Prefer few substantive sections over many thin ones.
We need to parse the job description and extract sections.
The posting includes:
- "The Role" paragraph describing role.
- "What You’ll Do" list of responsibilities (bullet points). Should be under Responsibilities.
- "Your Skills & Abilities (Required Qualifications)" list of required qualifications. Could be under Requirements or Qualifications. The instruction says we can use sections like Requirements, Qualifications, Skills. We need to decide which sections to output. We have required qualifications list; also "What Can Give You a Competitive Advantage (Preferred Qualifications)" list.
- There's also "This job may be eligible for relocation benefits." That's a benefit? Also "GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP..." That's a note but maybe we can drop as boilerplate? It's not exactly EEO but it's a restriction. Might be considered relevant but maybe we can keep as a short paragraph under Benefits? It's not a benefit but a condition. Might be considered "Other Information". However instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The immigration sponsorship note is not exactly EEO but could be considered legal? Might be considered a restriction; but it's part of the posting. The instruction says remove legal boilerplate. This is a legal statement about sponsorship. Likely we should remove it. Also "For a California-only role, use: Compensation: ..." includes compensation details. That is Pay section. So we should include Pay section with salary range and bonus potential. Also "Benefits Overview" paragraph about benefits. So we can include Benefits section.
- There's also "About GM", "Why Join Us", "Benefits Overview", "Non-Discrimination and Equal Employment Opportunities (U.S.)", "Accommodations". Those are boilerplate/EEO etc. Should be removed.
Thus we need sections: About the role (maybe "About the role" heading), Responsibilities, Requirements (or Qualifications), Skills (maybe combine required and preferred?), Benefits, Pay. Possibly also "Preferred Qualifications" as a subsection under Requirements or Skills. But we need to avoid many thin sections. Could combine required and preferred under "Qualifications" with two sublists? But instruction: use
for section headings. Could have separate headings for Required Qualifications and Preferred Qualifications if they have content. That's okay but we need to avoid many thin sections. However we have two distinct lists; we could combine them under "Qualifications" with two maybe with headings inside? But we cannot add extra headings besides . Could embed a
saying "Preferred qualifications:" then list. That's acceptable.
Thus sections:
- About the role (The Role paragraph)
- Responsibilities (What You’ll Do)
- Qualifications (Required Qualifications + Preferred Qualifications)
- Benefits (Benefits Overview + relocation benefits note maybe)
- Pay (Compensation details)
We should not include Schedule as not mentioned.
We need to ensure we preserve all substantive information: The role paragraph, responsibilities bullet list, required qualifications bullet list, preferred qualifications bullet list, benefits overview paragraph, relocation benefits note, compensation details (salary range, bonus potential). Also maybe note about "This job may be eligible for relocation benefits." That's a benefit.
We need to format responsibilities as
- each bullet.
Similarly required qualifications as
- .
Preferred qualifications as
- maybe under same section with a preceding
indicating "Preferred qualifications:".
Benefits: we have "Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources." plus "This job may be eligible for relocation benefits." We'll combine into a
maybe two paragraphs or one
with both sentences.
Pay: "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."
We need to output only HTML fragment, no /, no markdown fences.
Thus final output:
About 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.
Responsibilities
- 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.
Qualifications
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 integrate bots/agents with enterprise systems (ITSM, HR, CRM, internal APIs) using secure REST/webhook patterns.
- Deep understanding of GCP 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.
Preferred qualifications:
- Deep experience leveraging Vertex AI Agent Builder, LangChain, or LlamaIndex on GCP to build enterprise-grade, multi-agent systems.
- Proven success migrating legacy enterprise workflows (e.g., Microsoft M365, Power Automate, SharePoint) into native GCP 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).
Benefits
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. This job may be eligible for relocation benefits.
Pay
Compensation: The compensation information is a good-faith estimate only.
for prose. Do NOT repeat job title as heading. Do NOT put Job ID/requisition numbers as headings. Remove boilerplate, navigation, legal, EEO, equal-opportunity, scam-warning, duplicated lines, application instructions. Preserve all substantive information; do not invent or summarize away detail. Include a section ONLY when posting has real, specific content for it—never emit heading followed by filler/placeholder text (e.g., "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless posting actually states them. Prefer few substantive sections over many thin ones. We need to parse the job description and extract sections. The posting includes: - "The Role" paragraph describing role. - "What You’ll Do" list of responsibilities (bullet points). Should be under Responsibilities. - "Your Skills & Abilities (Required Qualifications)" list of required qualifications. Could be under Requirements or Qualifications. The instruction says we can use sections like Requirements, Qualifications, Skills. We need to decide which sections to output. We have required qualifications list; also "What Can Give You a Competitive Advantage (Preferred Qualifications)" list. - There's also "This job may be eligible for relocation benefits." That's a benefit? Also "GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP..." That's a note but maybe we can drop as boilerplate? It's not exactly EEO but it's a restriction. Might be considered relevant but maybe we can keep as a short paragraph under Benefits? It's not a benefit but a condition. Might be considered "Other Information". However instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The immigration sponsorship note is not exactly EEO but could be considered legal? Might be considered a restriction; but it's part of the posting. The instruction says remove legal boilerplate. This is a legal statement about sponsorship. Likely we should remove it. Also "For a California-only role, use: Compensation: ..." includes compensation details. That is Pay section. So we should include Pay section with salary range and bonus potential. Also "Benefits Overview" paragraph about benefits. So we can include Benefits section. - There's also "About GM", "Why Join Us", "Benefits Overview", "Non-Discrimination and Equal Employment Opportunities (U.S.)", "Accommodations". Those are boilerplate/EEO etc. Should be removed. Thus we need sections: About the role (maybe "About the role" heading), Responsibilities, Requirements (or Qualifications), Skills (maybe combine required and preferred?), Benefits, Pay. Possibly also "Preferred Qualifications" as a subsection under Requirements or Skills. But we need to avoid many thin sections. Could combine required and preferred under "Qualifications" with two sublists? But instruction: use
for section headings. Could have separate headings for Required Qualifications and Preferred Qualifications if they have content. That's okay but we need to avoid many thin sections. However we have two distinct lists; we could combine them under "Qualifications" with two maybe with headings inside? But we cannot add extra headings besides . Could embed a
saying "Preferred qualifications:" then list. That's acceptable.
Thus sections:
- About the role (The Role paragraph)
- Responsibilities (What You’ll Do)
- Qualifications (Required Qualifications + Preferred Qualifications)
- Benefits (Benefits Overview + relocation benefits note maybe)
- Pay (Compensation details)
We should not include Schedule as not mentioned.
We need to ensure we preserve all substantive information: The role paragraph, responsibilities bullet list, required qualifications bullet list, preferred qualifications bullet list, benefits overview paragraph, relocation benefits note, compensation details (salary range, bonus potential). Also maybe note about "This job may be eligible for relocation benefits." That's a benefit.
We need to format responsibilities as
- each bullet.
Similarly required qualifications as
- .
Preferred qualifications as
- maybe under same section with a preceding
indicating "Preferred qualifications:".
Benefits: we have "Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources." plus "This job may be eligible for relocation benefits." We'll combine into a
maybe two paragraphs or one
with both sentences.
Pay: "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."
We need to output only HTML fragment, no /, no markdown fences.
Thus final output:
About 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.
Responsibilities
- 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.
Qualifications
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 integrate bots/agents with enterprise systems (ITSM, HR, CRM, internal APIs) using secure REST/webhook patterns.
- Deep understanding of GCP 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.
Preferred qualifications:
- Deep experience leveraging Vertex AI Agent Builder, LangChain, or LlamaIndex on GCP to build enterprise-grade, multi-agent systems.
- Proven success migrating legacy enterprise workflows (e.g., Microsoft M365, Power Automate, SharePoint) into native GCP 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).
Benefits
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. This job may be eligible for relocation benefits.
Pay
Compensation: The compensation information is a good-faith estimate only.
. Could embed a
saying "Preferred qualifications:" then list. That's acceptable. Thus sections: - About the role (The Role paragraph) - Responsibilities (What You’ll Do) - Qualifications (Required Qualifications + Preferred Qualifications) - Benefits (Benefits Overview + relocation benefits note maybe) - Pay (Compensation details) We should not include Schedule as not mentioned. We need to ensure we preserve all substantive information: The role paragraph, responsibilities bullet list, required qualifications bullet list, preferred qualifications bullet list, benefits overview paragraph, relocation benefits note, compensation details (salary range, bonus potential). Also maybe note about "This job may be eligible for relocation benefits." That's a benefit. We need to format responsibilities as
- each bullet.
Similarly required qualifications as
- .
Preferred qualifications as
- maybe under same section with a preceding
indicating "Preferred qualifications:". Benefits: we have "Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources." plus "This job may be eligible for relocation benefits." We'll combine into a
maybe two paragraphs or one
with both sentences. Pay: "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." We need to output only HTML fragment, no /, no markdown fences. Thus final output:
About 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.
Responsibilities
- 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.
Qualifications
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 integrate bots/agents with enterprise systems (ITSM, HR, CRM, internal APIs) using secure REST/webhook patterns.
- Deep understanding of GCP 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.
Preferred qualifications:
- Deep experience leveraging Vertex AI Agent Builder, LangChain, or LlamaIndex on GCP to build enterprise-grade, multi-agent systems.
- Proven success migrating legacy enterprise workflows (e.g., Microsoft M365, Power Automate, SharePoint) into native GCP 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).
Benefits
From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. This job may be eligible for relocation benefits.
Pay
Compensation: The compensation information is a good-faith estimate only.
- maybe under same section with a preceding
- .
Preferred qualifications as