Senior GenAI Model Risk Validator

The Hartford; Hartford (CT); On-site; USD 108,000 - 162,000; Full time

Job summary

The Hartford is seeking a Sr Analyst in Model Risk Management to lead validation of GenAI and agentic AI models across the enterprise. You will review, challenge, and validate models to meet internal standards, regulatory expectations, and ethical AI principles.

Responsibilities include designing challenger solutions, testing frameworks, and governance for findings. Strong Python/SQL skills and insurance domain knowledge are a plus.

Qualifications

• Advanced degree in AI/ML or related field (MS/PhD).
• 3+ years in ML/DS with 1+ years in GenAI/agentic AI.
• P&C/Group/Life insurance knowledge is a plus.
• Strong programming experience in Python, SQL, Git.
• GenAI concepts: prompt engineering, RAG, LLM internals, multi-agent systems.
• Cloud/AI tools: GCP/Vertex AI, ADK, LangChain/LangGraph, HuggingFace, OpenAI APIs.

Responsibilities

• Perform GenAI and agentic AI model validations across business units.
• Ensure model calculations and methods are appropriate for intended use.
• Design testing methods for summarization, QA, search, data synthesis, and LLM evaluation.
• Assess data inputs, prompts, context engineering for accuracy and appropriateness.
• Develop and improve GenAI validation framework and metrics.
• Collaborate with Data Science teams to align model risk practices.
• Stay updated on AI governance standards and regulatory expectations.
• Document findings and remediation steps with clear reports.

Skills

GenAI/agentic AI

Python

SQL

Git

ML/DS experience

Insurance domain knowledge

Education

MS or PhD in AI/ML/CS

Tools

Vertex AI

uAgent Development Kit (ADK)

LangChain/LangGraph

HuggingFace

OpenAI APIs

SageMaker/AWS

Job description

The Hartford is seeking a Sr Analyst in Model Risk Management to lead validation of GenAI and agentic AI models across the enterprise. You will review, challenge, and validate models to meet internal standards, regulatory expectations, and ethical AI principles.

Responsibilities include designing challenger solutions, testing frameworks, and governance for findings. Strong Python/SQL skills and insurance domain knowledge are a plus.