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Verisk Analytics seeks a Senior AI Engineer to lead the design and delivery of complex AI solutions within our enterprise data platform. You will define standards, mentor engineers, and bridge business needs with production AI systems.
The role requires deep expertise in LLMs, agentic architectures, and enterprise data integration across AWS, Snowflake, and ThoughtSpot. You will collaborate with data engineers, architects, and stakeholders to shape solutions.
We are seeking a Senior AI Engineer to lead the design and delivery of complex AI solutions across our enterprise data platform. You will define technical standards, mentor junior engineers, and act as a key bridge between business requirements and production AI systems. Deep expertise in LLMs, agentic architectures, and enterprise data integration (AWS, Snowflake, ThoughtSpot) is essential.
About Verisk
Verisk Analytics is a global supplier of risk assessment services and decision analytics for customers across insurance, healthcare, financial services, and supply chain. We are a thriving public company with offices worldwide, continually expanding into new markets with excellent growth potential. At Verisk, you will be part of an organisation committed to the long-term interests of our stakeholders and communities.
Lead the technical design and delivery of complex, multi-component AI systems across our enterprise data platform.
Define architectural patterns and engineering standards for AI development — RAG, agents, LLM integrations, and MCP-based enterprise connectivity.
Drive secure, scalable integrations between AI models and enterprise data systems including Snowflake, AWS (SageMaker, Bedrock, S3), and ThoughtSpot.
Own end-to-end AI solution quality — including evaluation frameworks, monitoring pipelines, cost governance, and production reliability.
Lead cross-functional collaboration with data engineers, platform architects, and business stakeholders to shape requirements and validate solutions.
Mentor and coach junior and mid-level engineers, conducting substantive code reviews and contributing to team technical growth.
Champion AI governance standards — security, data access, PII, prompt injection, and responsible deployment practices.
Proactively identify and resolve technical risks and architectural gaps; communicate escalations clearly to engineering leadership.
Contribute to hiring processes — interviewing candidates and helping define role expectations.
Lead knowledge-sharing sessions and represent the team in technical discussions with senior stakeholders.
You will work within the following core technology environment:
Cloud Platform: AWS (S3, EC2, Lambda, SageMaker, Bedrock, IAM)
Data Warehouse: Snowflake (Snowpark, virtual warehouses, stages, streams)
Analytics & BI: ThoughtSpot
Search & Vector: OpenSearch, pgvector (Postgres)
LLM Providers: OpenAI, Anthropic / Claude, AWS Bedrock
AI Connectivity: Model Context Protocol (MCP) servers and integrations
Version Control & Project Tooling: Bitbucket, Jira, Confluence
Dev Tooling: Docker, Python, AI coding assistants (Cursor, GitHub Copilot, Claude Code)
We offer: