Model Validation Senior Manager

This role focuses on leading the end-to-end validation of AI, Generative AI (GenAI), and Agentic AI solutions for clients across various industries. The Senior Manager will design and execute validation plans, challenge model design, validate performance, and assess trustworthiness aspects like bias and explainability. The role also involves developing automated validation processes and mentoring teams, with a strong emphasis on responsible AI deployment and regulatory compliance.

What you'd actually do

  1. 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.
  2. Design and execute fit-for-purpose validation plans (testing strategy, acceptance criteria, documentation requirements, and traceability) aligned to broader risk management processes for AI.
  3. Perform effective independent challenge of model design choices, data suitability, assumptions, limitations, and intended use.
  4. 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).
  5. 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).

Skills

Required

  • Advanced Python skills
  • Experience with GenAI frameworks and components such as Hugging Face, OpenAI APIs, Llama models, Gemini, Claude, Granite, retrieval-augmented generation (RAG), and Stable Diffusion
  • Experience with Agentic AI frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, and CrewAI
  • 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
  • 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

Nice to have

  • 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

What the JD emphasized

  • AI, Generative AI (GenAI), and Agentic AI solutions
  • model validation
  • AI responsibly
  • independent challenge
  • model performance and stability
  • GenAI and Agentic AI behaviors and controls
  • trustworthiness topics
  • AI best practices
  • sound engineering judgment

Other signals

  • model validation
  • AI risk management
  • GenAI and Agentic AI