Manager, Technology Risk Consulting Artificial Intelligence and Emerging Technology Risk

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Role Summary

The Manager AI & Emerging Technology Risk is a client-facing consulting leader who combines AI engineering and solution architecture with deep understanding of Risk functions (e.g. operational risk model risk management compliance fraud/financial crime credit risk and enterprise governance). The role leads engagements to design develop and deploy production-grade AI/GenAI solutions that are secure auditable and aligned to regulatory expectationswhile advising executives and technology teams on risk-by-design operating models controls and governance. The Manager partners with client engineering data and risk stakeholders to translate business and control requirements into implementable architectures drive delivery from prototype to production and operationalize monitoring and governance across data models and platforms.

Key Responsibilities

AI Engineering & GenAI Solution Delivery (Risk Use Cases)

• Design and implement AI/GenAI solutions for Risk use cases (e.g. risk intelligence control testing issue management fraud detection regulatory response) across data ingestion feature engineering model development evaluation and deployment
• Engineer secure reference architectures for AI platforms (cloud data/feature stores model registry vector databases API gateways) including GenAI patterns (RAG tool use agents) with embedded guardrails for access prompt/data leakage isolation and resilience
• Operationalize Responsible AI and Model Risk practices through measurable tests (bias/fairness robustness explainability) documentation (model cards data sheets) human-in-the-loop design and continuous monitoring/drift management

Risk Governance Controls & Regulatory Alignment

• Translate Risk requirements into technical control objectives and implementation details across the AI lifecycle (data model platform SDLC) including evidence collection and audit-ready traceability
• Map AI/GenAI risks and controls to enterprise risk management (ERM) and technology risk frameworks coordinating with Model Risk Compliance Privacy and Security teams to meet policy and regulatory expectations
• Design and implement AI governance operating models (intake use-case classification approval gates RACI and exception handling) that integrate with SDLC/MLOps release processes for both ML and LLM-based systems

MLOps/LLMOps Platform Engineering & Production Deployment

• Partner with client engineering and data teams to design end-to-end system flows (APIs eventing data pipelines) and integrate AI services into Risk platforms and workflows
• Build and assess MLOps/LLMOps practices including CI/CD infrastructure-as-code automated testing/evaluation model/Prompt/versioning and release gates aligned to Risk and control requirements
• Identify gaps in production readiness for AI systems (observability drift/quality monitoring secrets management throughput/latency failover and incident response) and implement pragmatic remediation patterns

Advisory & Enablement

• Lead client workshops discovery sessions and design reviews to align Risk stakeholders and engineering teams on target-state AI/GenAI architectures and delivery approach
• Develop risk-focused training materials and deliver enablement sessions for technical and non-technical audiences including executive briefings
• Coach and develop junior team members providing technical oversight and quality control across AI engineering governance and risk deliverables
• Produce high-quality client deliverables (risk assessments architecture patterns implementation roadmaps and executive summaries) with clear recommendations trade-offs and implementation steps
• Support engagement management by helping scope workstreams define milestones manage stakeholder expectations and ensure on-time delivery and quality
• Contribute to business development through proposal writing solution positioning and creation of reusable assets (playbooks accelerators reference architectures) for Risk-focused AI offerings

Experience Skills & Qualifications

• Bachelors or Masters degree in Computer Science Engineering Data Science Information Systems or related field (or equivalent practical experience)
• 57 years of experience delivering production technology solutions with meaningful depth in AI/ML or GenAI engineering and experience in risk compliance audit or other regulated environments
• Job relevant certification (i.e. Azure Aws or AI certifications)

Preferred Qualifications

• Hands-on experience with modern ML/GenAI stacks (e.g. Python model development frameworks embedding/RAG workflows) and the ability to design for evaluation safety and controllability
• Experience engineering and/or assessing AI platforms on cloud infrastructure including IAM encryption/secrets management network controls data governance/lineage and environment segregation
• Strong software engineering fundamentals: APIs and service design data pipelines testing code review CI/CD and operating production services
• Ability to translate architecture decisions into Risk impacts (control effectiveness regulatory exposure third-party risk operational resilience) and define concrete technical mitigations
• Consulting delivery skills: requirements elicitation workplan development facilitation and managing dependencies across client teams
• Experience producing model/GenAI governance artifacts (validation support testing results lineage change logs) and partnering with Model Risk and audit stakeholders through approvals
• Executive-ready communicator with experience translating technical concepts into clear business and Risk narratives influencing stakeholders and presenting recommendations to senior leadership

At RSM we offer a competitive benefits and compensation package for all our offer flexibility in your schedule empowering you to balance lifes demands while also maintaining your ability to serve more about our total rewards at applicants will receive consideration for employment as RSM does not tolerate discrimination and/or harassment based on race; color; creed; sincerely held religious beliefs practices or observances; sex (including pregnancy or disabilities related to nursing); gender; sexual orientation; HIV Status; national origin; ancestry; familial or marital status; age; physical or mental disability; citizenship; political affiliation; medical condition (including family and medical leave); domestic violence victim status; past current or prospective service in the US uniformed service; US Military/Veteran status; pre-disposing genetic characteristics or any other characteristic protected under applicable federal state or local law.

Accommodation for applicants with disabilities is available upon request in connection with the recruitment process and/or employment/ is committed to providing equal opportunity and reasonable accommodation for people with disabilities. If you require a reasonable accommodation to complete an application interview or otherwise participate in the recruiting process please call us at or send us an email at .

RSM does not intend to hire entry level candidates who will require sponsorship now OR in the future (i.e. F-1 visa holders). If you are a recent U.S. college / university graduate possessing 1-2 years of progressive and relevant work experience in a same or similar role to the one for which you are applying excluding internships you may be eligible for hire as an experienced associate.

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At RSM an employees pay at any point in their career is intended to reflect their experiences performance and skills for their current role. The salary range (or starting rate for interns and associates) for this role represents numerous factors considered in the hiring decisions including but not limited to education skills work experience certifications location etc. As such pay for the successful candidate(s) could fall anywhere within the stated range.