Director – Technology Risk Consulting – Artificial Intelligence, Emerging Technology

Role Overview

• The Director, AI & Emerging Technology Risk provides strategic leadership across client delivery, pre‑sales, and advisory services related to artificial intelligence and emerging technologies.
• 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.
• 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.
• 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.
• 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, delivery approach, assumptions, pricing inputs, and risk-managed implementation plan.
• Run client workshops and executive presentations that walk through architectures, control designs, and delivery plans—bridging 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.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Risk, or related discipline (or equivalent practical experience)
• 8–10+ 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.)
• 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

Tech Stack

• AWS
• Azure
• Cloud
• Cyber Security
• SDLC

Benefits

• flexibility in your schedule
• empowering you to balance life’s demands