Job Opportunities API

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)