Accenture
Consultant Engineer - AI Governance, Model Risk & Compliance
Accenture, Milwaukee, Wisconsin, United States, 53244
In Strategy & Consulting we work with C-suite executives, leaders and boards of the world’s leading organizations, helping them reinvent every part of their enterprise to drive greater growth, enhance competitiveness, implement operational improvements, reduce cost, deliver sustainable 360° stakeholder value, and set a new performance frontier for themselves and the industry in which they operate.
We are :
Finance Risk Compliance (FRC), and we give Chief Financial Officers, Chief Risk Officers, Chief Compliance Officers, Chief Data Officers and their execs the sounding board they need and the industry best practices they seek. You are :
A consultant who has helped build and deliver transformative AI / ML and GenAI initiatives in the Financial Services industry (banking, insurance, capital markets). You bring client-facing and consulting capabilities , experience operationalizing AI — from vendor selection and prototyping to testing, automation, deployment, and monitoring. The work : Support client engagements focused on deploying AI / GenAI solutions, navigating regulatory landscapes, and delivering measurable business outcomes Contribute to AI initiatives including evaluating vendor platforms, designing and testing prototypes, integrating enterprise data pipelines, and automating workflows Assist leads who are 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 Support the 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 Aid in evaluating third-party AI platforms, LLM providers, and emerging tools for fit, functionality, compliance, and risk exposure Travel as needed based on client expectations. Here’s what you need : Minimum of 3 years’ banking or consulting experience delivering AI / ML or model lifecycle solutions in Financial Services and / or Insurance , including hands-on client delivery. Minimum of 3 years’ experience supporting the testing, automation, monitoring, or deployment of AI / ML models and applications in production environments Minimum of 2 years’ experience implementing model risk governance frameworks , including controls for model validation, bias mitigation, and performance monitoring Experience working with Python and understanding of, but not limited to, 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 if : Consulting experience from a top competitor firm is highly preferred. 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 Exposure to 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 Accenture is an EEO and Affirmative Action Employer of Veterans / Individuals with Disabilities. We believe that no one should be discriminated against because of their differences.All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
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Finance Risk Compliance (FRC), and we give Chief Financial Officers, Chief Risk Officers, Chief Compliance Officers, Chief Data Officers and their execs the sounding board they need and the industry best practices they seek. You are :
A consultant who has helped build and deliver transformative AI / ML and GenAI initiatives in the Financial Services industry (banking, insurance, capital markets). You bring client-facing and consulting capabilities , experience operationalizing AI — from vendor selection and prototyping to testing, automation, deployment, and monitoring. The work : Support client engagements focused on deploying AI / GenAI solutions, navigating regulatory landscapes, and delivering measurable business outcomes Contribute to AI initiatives including evaluating vendor platforms, designing and testing prototypes, integrating enterprise data pipelines, and automating workflows Assist leads who are 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 Support the 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 Aid in evaluating third-party AI platforms, LLM providers, and emerging tools for fit, functionality, compliance, and risk exposure Travel as needed based on client expectations. Here’s what you need : Minimum of 3 years’ banking or consulting experience delivering AI / ML or model lifecycle solutions in Financial Services and / or Insurance , including hands-on client delivery. Minimum of 3 years’ experience supporting the testing, automation, monitoring, or deployment of AI / ML models and applications in production environments Minimum of 2 years’ experience implementing model risk governance frameworks , including controls for model validation, bias mitigation, and performance monitoring Experience working with Python and understanding of, but not limited to, 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 if : Consulting experience from a top competitor firm is highly preferred. 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 Exposure to 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 Accenture is an EEO and Affirmative Action Employer of Veterans / Individuals with Disabilities. We believe that no one should be discriminated against because of their differences.All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
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