Senior Gen AI Software Engineer

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)
• Bachelor's degree or higher in Artificial Intelligence, Computer Science, Data Science, Software Engineering, or a related technical field (or equivalent practical experience).
• At least 4 years of professional experience in software engineering or AI engineering, including at least 2–3 years designing, developing, and deploying AI/ML solutions in production environments.
• Strong expertise in agentic AI systems, including multi-agent architectures, orchestration frameworks (e.g., LangGraph, AutoGen), and state management.
• Experience designing secure enterprise AI integrations using MCP or similar integration patterns.
• Advanced knowledge of vector search and RAG architectures using OpenSearch (kNN, hybrid search) and pgvector.
• Hands-on experience with LLM fine-tuning (LoRA, PEFT, RLHF) and selecting appropriate approaches across fine-tuning, prompt engineering, and RAG.
• Advanced experience with AWS AI services (including SageMaker and Bedrock) and Snowflake (Snowpark, Dynamic Tables, feature pipelines) for scalable AI solutions.
• Experience implementing AI evaluation, observability, security, governance, and compliance frameworks for production systems.
• Strong cloud engineering skills, including containers, Infrastructure as Code (IaC), CI/CD, and cost-optimized deployments.
• Excellent communication, stakeholder management, and mentoring skills, with the ability to influence technical decisions across cross-functional teams.

We offer

• The opportunity to build production-grade AI solutions using the latest LLM, RAG, and agentic AI technologies on AWS and Snowflake.
• A collaborative, international environment where you'll work closely with software engineers, solution architects, and business stakeholders to solve real-world challenges.
• Exposure to modern AI tooling, cloud-native architectures, and the freedom to influence technical design and engineering best practices.
• 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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