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, pre‑sales, 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 go‑to‑market strategy, supporting pre‑sales 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 resilience-grounded 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 ERM-mapping 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 compliance-producing 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 practices-cloud landing zones, APIs, data pipelines, CI/CD, model registries, and deployment strategies-to 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 implementation-owning 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

Go‑to‑Market 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 development-scoping, staffing model,…