Model Validation Senior Manager
- 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.
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to mentor and provide clear guidance to others 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.
- 12+ years of 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.
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.
- Ability to travel up to 15%, based on the work you do and the clients and industries/sectors you serve.
- 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
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