Senior GxP AI Validation Consultant

Job Summary

We are seeking a highly experienced and detail-oriented AI Model Evaluation Consultant with strong expertise in validating AI/ML models, Generative AI (GenAI) systems, and multiagent workflows within GxP-regulated and quality-critical environments. The ideal candidate will ensure the reliability, fairness, robustness, and regulatory compliance of AI solutions while supporting cross-functional teams in designing, testing, and maintaining production-ready, inspection-ready AI systems.

Your Role

This role is responsible for leading AI model evaluation and validation activities across the full model lifecycle, including model development, training, testing, deployment, and postdeployment monitoring, in alignment with GxP principles, risk-based validation, and data integrity expectations. The consultant will play a key role in embedding Responsible AI, quality-by-design, and governance-by-design practices, enabling the safe, trustworthy, and explainable use of AI and agent-based solutions in regulated life sciences and pharmaceutical contexts.

Your key responsibilities

• Support development of AI/ML and Agentic AI strategies by providing analysis, validation insights, and readiness assessments.
• Perform AI/ML model evaluation and validation across development, training, testing, and deployment phases.
• Evaluate model performance using precision, recall, accuracy, F1score, and confusion matrices.
• Assess model behavior across datasets, edge cases, and failure scenarios to identify bias, drift, and instability.
• Demonstrate strong understanding of supervised and unsupervised learning models, including classification, regression, clustering, and anomaly detection.
• Conduct handson evaluation of GenAI and LLM-based systems, including prompt behavior, response quality, and consistency.
• Design and execute testing strategies for AI agents and multiagent workflows, covering orchestration logic, tool invocation, and output validation.
• Use LangChain, LangGraph, and Langfuse for agent workflows, observability, traceability, and evaluation logging.
• Collaborate with data scientists and engineers to identify model improvement opportunities and risk mitigations.
• Document evaluation results, limitations, risks, and acceptance criteria in a clear, audit-ready manner.

Qualifications

• Bachelors or masters degree in Life Sciences, Engineering, or related field.
• 5+ years of experience in AI/ML, GenAI, software testing, validation, or quality engineering roles.
• Experience creating user stories, test scripts, validation plans, or AI solution prototypes.
• Exposure to cloud ecosystems such as Azure, AWS, or GCP.
• Consulting or client-facing experience preferred.
• Excellent communication, documentation, and stakeholder management skills.

Must-Have Skills And Attributes

• Strong understanding of ML models, LLMs, GenAI workflows, agentic systems, and evaluation techniques.
• Strong foundation in machine learning concepts and model evaluation techniques.
• Handson experience with: Precision, Recall, Confusion Matrix, ROC/AUC, Supervised and Unsupervised ML models
• Practical experience with LangChain, LangGraph, and Langfuse.
• Experience evaluating GenAI / LLM-based applications and agents.
• Strong documentation, analytical, and stakeholder communication skills.
• Experience designing test cases, user stories, and acceptance criteria for AI/ML-based systems.
• Ability to validate AI outputs, evaluate accuracy, detect bias, and assess model reliability under varied conditions.
• Hands-on skills in building prototypes, test harnesses, and demo environments.
• Strong stakeholder management, analytical thinking, and structured communication skills.
• Familiarity with version control, prompt engineering fundamentals, and AI-assisted testing tools is preferred.
• Strong knowledge of GxP regulations (FDA 21 CFR Part 11, EU Annex 11)
• GAMP 5 methodology and system development life cycle (SDLC)
• CSV documentation: URS, FRS, IQ/OQ/PQ, Traceability Matrix, Validation Plans
• Understanding of data integrity principles and electronic records/e-signatures compliance
• Ability to collaborate with cross-functional teams (QA, IT, Manufacturing, Labs)
• Experience in client-facing roles, managing expectations and delivering solutions
• Strong communication and presentation skills
• Experience in IT project management and validation planning
• Ability to troubleshoot application issues and recommend solutions
• Familiari…