Principal Gen AI Software Engineer

We are looking for a Principal AI Engineer to serve as our highest-level individual technical contributor in AI engineering. You will set the technical direction for AI across the organisation, drive architectural decisions, own cross-functional delivery of strategic AI initiatives, and establish the engineering culture and standards that scale our capabilities. This is a role for a recognized expert who can lead from the front — hands-on, opinionated, and deeply trusted.

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.

Responsibilities

• Set the technical direction for AI engineering across the organization — establishing architecture principles, technology choices, and long-term capability roadmap.

• Own the design of the most complex, strategic AI initiatives — from early ideation through production delivery and ongoing evolution.

• Define and enforce engineering standards for AI systems: security, scalability, evaluation, observability, and governance.

• Lead enterprise AI integration strategy — connecting AI models to Snowflake, AWS, ThoughtSpot, and broader data ecosystems via MCP and custom integrations.

• Act as the primary technical authority on LLM systems, agentic architectures, RAG, and emerging AI frameworks within the organization.

• Drive cross-functional alignment between engineering, data, product, and business teams on AI strategy and priorities.

• Champion AI governance at the organizational level — data access, PII, security, cost controls, and responsible deployment.

• Lead code reviews and technical design reviews across teams; elevate the overall quality and consistency of AI engineering practice.

• Present technical vision and AI strategy to senior leadership and external stakeholders.

• Build and scale the AI engineering function — mentoring principals-in-training, defining levelling criteria, and contributing to hiring and team structure.

• Represent Verisk AI engineering externally — thought leadership, technical writing, or industry engagement where relevant.

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)

Qualifications

• Bachelor's degree or higher in AI, Computer Science, Data Science, Software Engineering, or a related field (or equivalent experience).
• 7+ years of software engineering experience, including 4+ years in AI/ML engineering, with demonstrated organizational impact.
• Proven track record of defining technical strategy, enterprise architecture, and engineering standards; external recognition (publications, speaking, or open source) is an advantage.
• Ability to define the long-term AI engineering strategy and technology roadmap, driving adoption of emerging AI capabilities where they deliver business value.
• Architects enterprise-scale AI platforms across AWS, Snowflake, ThoughtSpot, MCP-connected systems, and hybrid cloud environments.
• Executive communication with the ability to clearly articulate AI strategy, technical vision, and complex concepts to senior leaders and diverse stakeholders.
• Strategic thinking that connects AI engineering decisions to long-term business objectives and anticipates future organizational needs.
• Influential leadership that shapes engineering culture, drives alignment, and builds consensus across teams and functions.
• Strong decision-making and sound judgement.
• Coaching and mentoring mindset, with a proven ability to develop senior engineering talent and strengthen organizational capability.

We offer:

• The opportunity to define and lead the enterprise AI strategy, shaping the adoption of cutting-edge LLM, agentic AI, RAG, and emerging AI technologies across the organization.
• Ownership of enterprise-scale AI architecture, platforms, and engineering standards spanning AWS, Snowflake, ThoughtSpot, and hybrid cloud environments.
• The autonomy to influence technology direction, governance, engineering culture, and long-term platform evolution while mentoring the next generation of AI leaders.
• A hybrid work model with flexible working hours. 
• A benefits package, including private health insurance, medical care, and a Multisport card.