Director Technology Risk Consulting Artificial Intelligence and Emerging Technology

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Role Summary

The Director AI & Emerging Technology Risk provides strategic leadership across client delivery presales and advisory services related to artificial intelligence and emerging technologies. This role blends AI expertise enterprise risk management technology risk leadership solution architecture and software development oversight to help clients innovate responsibly while managing risk. The Director plays a key role in shaping gotomarket strategy supporting presales efforts and serving as an executive advisor throughout the client lifecycle.

Artificial Intelligence & Emerging Technology Leadership

• Advise executive stakeholders on AI and emerging-technology risk across governance ethics security privacy and operational resiliencegrounded in how models are built deployed and monitored in production
• Lead client decisioning on GenAI/ML adoption by translating business use cases into implementable architectures control requirements and delivery roadmaps (people/process/technology)
• Track evolving model capabilities platforms and threat/regulatory trends to continuously refine solution patterns controls and sales positioning for risk-focused AI offerings

Enterprise Risk & Technology Risk Strategy

• Design and operationalize AI/technology risk frameworks aligned to ERMmapping controls to the AI/ML lifecycle (data training evaluation deployment monitoring change management)
• Assess enterprise-wide AI impacts across cybersecurity privacy model risk management (MRM) third-party risk and complianceproducing actionable remediation plans and control implementation backlogs
• Present AI risk posture risk appetite alignment and control maturity to Boards and executive committees using clear metrics (KRIs/KPIs) model inventories and audit-ready documentation

Solutions Architecture & Software Oversight

• Architect AI-enabled solutions for risk consulting clients (including GenAI/RAG patterns) with secure-by-design scalable and governable reference architectures
• Evaluate SDLC and MLOps practicescloud landing zones APIs data pipelines CI/CD model registries and deployment strategiesto identify risk control gaps and engineering fixes
• Embed risk-by-design into build plans: threat modeling privacy engineering evaluation/validation protocols human-in-the-loop controls monitoring/alerting and incident response runbooks

Client Delivery & Practice Leadership

• Lead AI risk and emerging-technology engagements from strategy to implementationowning delivery plans sprint execution stakeholder management and outcomes
• Establish delivery governance (scope RAID quality gates model validation checkpoints) and ensure solutions are production-ready auditable and defensible
• Build and mentor cross-functional teams (risk data science engineering security) and provide technical leadership across Managers and Senior Managers
• Develop reusable accelerators (reference architectures control libraries evaluation harnesses templates) and publish market-facing thought leadership to scale delivery and sales
• Drive account expansion by identifying adjacent risk opportunities quantifying value and partnering with client leaders to turn delivery success into follow-on sales

GotoMarket Leadership

• Own delivery sales for AI risk pursuits: qualify opportunities shape deal strategy and lead solutioning as the senior AI engineering/risk SME
• Define and package AI risk solution offerings (e.g. GenAI governance MRM uplift secure RAG AI SDLC/MLOps controls) with clear value propositions and deliverables
• Lead proposal developmentscoping staffing model delivery approach assumptions pricing inputs and risk-managed implementation plan
• Run client workshops and executive presentations that walk through architectures control designs and delivery plansbridging engineering details to risk outcomes
• Translate transformation goals into implementable AI risk solutions aligned to regulatory guidance internal governance and target-state technology architecture
• Build trusted C-level relationships and maintain pipeline by connecting delivery success to measurable risk reduction audit readiness and operational resilience

Experience Skills & Qualifications

• Bachelors or Masters degree in Computer Science Engineering Data Science Risk or related discipline (or equivalent practical experience)
• 810 years leading technology risk and/or AI engineering delivery in consulting or industry including ownership of large client programs
• Job relevant certification (ie Azure Aws AI certifications etc.)

Preferred Qualifications

• Deep knowledge of modern AI/ML and GenAI (LLMs RAG evaluation safety) and the ability to translate that into concrete risk controls and implementation patterns
• Proven delivery sales experience: shaping pursuits leading solutioning contributing to pricing and presenting to executive buyers
• Strong understanding of cloud and data architecture SDLC and MLOps/LLMOps (CI/CD IaC observability model registry feature stores policy-as-code)
• Demonstrated ability to embed governance security privacy and model risk management early in design/build and to stand up audit-ready evidence and controls
• Executive-level communicator who can translate between engineers risk leaders regulators/auditors and business stakeholders; comfortable owning both delivery and commercial outcomes

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.

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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.