Accenture
Manager or Senior Manager - AI/GenAI Governance, Model Risk & Compliance Enginee
Accenture, Walnut Creek, California, United States, 94598
Overview
Manager or Senior Manager - AI/GenAI Governance, Model Risk & Compliance Engineer at Accenture. An experienced senior consulting executive who has built and delivered transformative AI/GenAI initiatives across Financial Services and/or Insurance, with strong client-facing and consulting capabilities, and a track record of operationalizing AI from vendor selection and prototyping to testing, automation, deployment, and monitoring. Responsibilities
Support and lead client engagements focused on deploying AI/GenAI solutions, navigating regulatory landscapes, and delivering measurable business outcomes Drive execution of AI initiatives by evaluating vendor platforms, designing and testing prototypes, integrating enterprise data pipelines, and automating workflows Assist in providing oversight across the model lifecycle — supporting development, independent validation, monitoring, and control enhancements for model and AI governance Partner with clients to test and deploy GenAI and traditional AI models, ensuring alignment with ethical AI principles, operational controls, and business context Help guide implementation of AI risk mitigation frameworks, addressing data security, privacy, access control, explainability, model bias, and monitoring Collaborate with technology teams to ensure seamless deployment and automation of AI/GenAI solutions in production environments Evaluate third-party AI platforms, LLM providers, and emerging tools for fit, functionality, compliance, and risk exposure Translate complex AI and model monitoring outputs into executive-ready insights, helping clients act on results in real time Travel as needed based on client expectations What you need
5 years of consulting experience from a large, competitor firm, delivering AI/ML or model lifecycle solutions in Financial Services and/or Insurance, including hands-on client delivery 5 years of experience supporting the testing, automation, monitoring, or deployment of AI/ML applications in production environments 3 years of experience implementing model risk governance frameworks, including controls for model validation, bias mitigation, and performance monitoring Experience with Python and familiarity with libraries like LangChain and Huggingface Bachelor’s or Master’s degree in a quantitative or technical discipline (e.g., Engineering, Information Systems, Applied Mathematics) Bonus points
You have experience in model validation, audit, or model risk management within a regulated Financial Services environment Prior experience working in or with regulatory bodies (e.g., OCC, FRB, OSFI, FDIC) in model supervision, AI governance, or data risk Experience managing deployment and risk controls for credit risk, AML/KYC, fraud detection, or marketing models Familiarity with leading AI/GenAI vendor platforms, including LLMs, open-source models, and APIs (e.g., OpenAI, Anthropic, Amazon Q, Microsoft Copilot) Hands-on experience with cloud environments (AWS, Azure, GCP) or MLOps tools for automating and monitoring AI pipelines Demonstrated understanding of data security principles, including data encryption, access management, PII handling, and compliance with GDPR/CCPA/OSFI B-13 Experience supporting business transformation through AI About compensation and diversity statements
Compensation at Accenture varies depending on a wide array of factors. Accenture provides a reasonable range of compensation for roles that may be hired in certain U.S. locations. We accept applications on an on-going basis and there is no fixed deadline to apply. Accenture is an Equal Opportunity Employer and is committed to creating an inclusive environment. See the company Equal Employment Opportunity statements for details.
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Manager or Senior Manager - AI/GenAI Governance, Model Risk & Compliance Engineer at Accenture. An experienced senior consulting executive who has built and delivered transformative AI/GenAI initiatives across Financial Services and/or Insurance, with strong client-facing and consulting capabilities, and a track record of operationalizing AI from vendor selection and prototyping to testing, automation, deployment, and monitoring. Responsibilities
Support and lead client engagements focused on deploying AI/GenAI solutions, navigating regulatory landscapes, and delivering measurable business outcomes Drive execution of AI initiatives by evaluating vendor platforms, designing and testing prototypes, integrating enterprise data pipelines, and automating workflows Assist in providing oversight across the model lifecycle — supporting development, independent validation, monitoring, and control enhancements for model and AI governance Partner with clients to test and deploy GenAI and traditional AI models, ensuring alignment with ethical AI principles, operational controls, and business context Help guide implementation of AI risk mitigation frameworks, addressing data security, privacy, access control, explainability, model bias, and monitoring Collaborate with technology teams to ensure seamless deployment and automation of AI/GenAI solutions in production environments Evaluate third-party AI platforms, LLM providers, and emerging tools for fit, functionality, compliance, and risk exposure Translate complex AI and model monitoring outputs into executive-ready insights, helping clients act on results in real time Travel as needed based on client expectations What you need
5 years of consulting experience from a large, competitor firm, delivering AI/ML or model lifecycle solutions in Financial Services and/or Insurance, including hands-on client delivery 5 years of experience supporting the testing, automation, monitoring, or deployment of AI/ML applications in production environments 3 years of experience implementing model risk governance frameworks, including controls for model validation, bias mitigation, and performance monitoring Experience with Python and familiarity with libraries like LangChain and Huggingface Bachelor’s or Master’s degree in a quantitative or technical discipline (e.g., Engineering, Information Systems, Applied Mathematics) Bonus points
You have experience in model validation, audit, or model risk management within a regulated Financial Services environment Prior experience working in or with regulatory bodies (e.g., OCC, FRB, OSFI, FDIC) in model supervision, AI governance, or data risk Experience managing deployment and risk controls for credit risk, AML/KYC, fraud detection, or marketing models Familiarity with leading AI/GenAI vendor platforms, including LLMs, open-source models, and APIs (e.g., OpenAI, Anthropic, Amazon Q, Microsoft Copilot) Hands-on experience with cloud environments (AWS, Azure, GCP) or MLOps tools for automating and monitoring AI pipelines Demonstrated understanding of data security principles, including data encryption, access management, PII handling, and compliance with GDPR/CCPA/OSFI B-13 Experience supporting business transformation through AI About compensation and diversity statements
Compensation at Accenture varies depending on a wide array of factors. Accenture provides a reasonable range of compensation for roles that may be hired in certain U.S. locations. We accept applications on an on-going basis and there is no fixed deadline to apply. Accenture is an Equal Opportunity Employer and is committed to creating an inclusive environment. See the company Equal Employment Opportunity statements for details.
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