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.
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)
- 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.
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