Senior Manager - Model Validation

Regulatory & Financial Risk - Senior Manager - Model Validation

Our Deloitte Regulatory, Risk & Forensic team helps client leaders translate multifaceted risk and an evolving regulatory environment into defensible actions that strengthen, protect, and transform their organizations. Join our team and use advanced data, AI, and emerging technologies with industry insights to help clients bring clarity from complexity and accelerate their path to value creation.

Work you'll do

You will lead model validation work for AI, Generative AI (GenAI), and Agentic AI solutions across client engagements. You will set the technical direction for validation approaches, manage and mentor teams, and provide senior-level oversight of deliverable quality. You will work across industries such as Financial Services, Life Sciences, and Technology, Media, and Telecom, helping clients strengthen model risk management practices and deploy AI responsibly.

Responsibilities include

• Lead end-to-end validation of AI, GenAI, and Agentic AI solutions, from initial review of objectives and data through production readiness and ongoing monitoring.
• Design and execute fit-for-purpose validation plans (testing strategy, acceptance criteria, documentation requirements, and traceability) aligned to broader risk management processes for AI.
• Perform effective independent challenge of model design choices, data suitability, assumptions, limitations, and intended use.
• Validate model performance and stability using appropriate methods (for example: benchmarking, back-testing where applicable, sensitivity and stress testing, error analysis, and scenario-based evaluation).
• Develop models (example: credit risk models) and conceptualize modernization of associated processes.
• Validate GenAI and Agentic AI behaviors and controls (for example: evaluation of response quality, hallucination and grounding checks for RAG, prompt and tool-use testing, guardrails, escalation paths, and audit logging).
• Assess trustworthiness topics and recommend mitigations (for example: bias and fairness considerations, explainability, robustness, privacy and security considerations, and operational controls).
• Develop and embed automated processes for model validation, monitoring, and reporting (for example: standardized test harnesses, evaluation pipelines, and model documentation templates).
• Serve as a key contributor to project planning and direction-prioritizing client goals, managing technical risks, and ensuring teams execute to plan.
• Translate technical findings into clear, decision-ready messages for client stakeholders, and influence decisions with evidence-based recommendations.
• Supervise, mentor, and develop team members through coaching, technical review, and hands-on support.
• Connect and collaborate with specialists across Deloitte to strengthen validation approaches and stay current on emerging AI methodologies.

The Team

Our Regulatory & Financial Risk offering supports clients' regulatory and compliance needs, balancing risk and regulatory requirements with enhancing business value and optimizing outcomes. We deliver enhanced value through strategic transformation, end-to-end implementation, and a focus on business-as-usual sustainability across processes, controls, and data & analytic infrastructures.

Qualifications

Required:

• Undergraduate degree in Computer Science, Data Science, Artificial Intelligence, Applied Mathematics, or a related field.
• Advanced Python skills; ability to guide production-quality code (readable, well-tested, with well-designed APIs).
• Experience with GenAI frameworks and components such as Hugging Face, OpenAI APIs, Llama models, Gemini, Claude, Granite, retrieval-augmented generation (RAG), and Stable Diffusion-particularly as relevant to evaluation, controls, and validation.
• Experience with Agentic AI frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, and CrewAI-particularly as relevant to tool-use testing, safety controls, and operational risk.
• Experience with at least 1 deep learning framework such as PyTorch or TensorFlow/Keras.
• Experience building and deploying AI solutions on AWS, Azure, or GCP; familiarity with containerization (Docker, Kubernetes) for scalable deployments.
• Strong understanding of ML/DL methods and architectures, performance assessment, and model validation.
• Expert understanding of AI best practices and sound engineering judgment for complex issues.
• Excellent written and verbal communication skills.
• Ability to lead teams effectively through coaching, technical direction, and quality assurance.
• Limited immigration sponsorship may be available.
• Ability to travel up to 15%, based on the work you do and the clients and industries/sectors you serve.

Preferred:

• Master's degree
• Industry specialization (for example: Financial Services)
• Experience with JavaScript
• GenAI and Agentic AI projects deployed to production
• Understanding of AI/GenAI/Agentic AI risks, bias, mitigation approaches, and responsible use
• Large-scale deep learning model training experience

For individuals assigned and/or hired to work in Washington State, Deloitte is required by law to include a reasonable estimate of the compensation range for this role. This compensation range is specific to Washington State and takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $175,700 to $292,900.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any depends on various factors, including, without limitation, individual and organizational performance.

Information for applicants with a need for accommodation: [1]

References