Experience:

• 8+ years of professional software development experience (Dotnet/React/Full-stack) with mentorship/team leadership experience
• Minimum 2 years of hands-on experience building applications using Generative AI or agentic AI systems

Role Focus:

• Architect and design production-ready applications leveraging Generative AI and agentic AI frameworks
• Build, deploy and monitor intelligent workflows using LLMs, multi-agent coordination, and orchestration pipelines
• Integrate new AI applications with traditional pre-existing applications
• Implement prompt engineering strategies, retrieval-augmented generation (RAG), and contextual memory systems
• Implement various AI coding techniques such as context-driven and spec-driven development
• Architect and implement AI agents capable of reasoning, planning, and multi-step task execution
• Implement and utilize Model Context Protocol (MCP) patterns for structured communication between agents, tools, and systems
• Provide mentoring and technical guidance to developers and other AI Engineers
• Develop evaluation pipelines to measure accuracy, safety, and performance of AI systems
• Optimize latency, cost efficiency, and scalability of AI-powered workflows
• Collaborate with product managers, data teams, and software engineers to deliver AI features
• Ensure reliability through testing, logging, monitoring, and observability of AI behavior
• Own architectural decisions, coding standards, and best practices
• Act as an AI trailblazer for development teams by promoting best practices, reusable patterns, and adopting AI-driven engineering approaches
• Apply AI governance principles to ensure responsible model usage, auditability, and transparency in AI workflows
• Support implementation of governance controls related to data handling, model behavior monitoring, and risk mitigation
• Research emerging AI tools and frameworks to continuously improve system capabilities
• Document AI workflows and maintain reproducible engineering processes

Nice to have:

• Experience deploying AI applications in cloud environments (preferably AWS)
• Familiarity with vector databases and knowledge retrieval architectures
• Experience working with Git, CI/CD pipelines, and production deployments
• Exposure to containerization and orchestration tools (Docker, Kubernetes)
• Experience implementing evaluation or monitoring pipelines for AI agents
• Knowledge of AI safety, guardrails, and responsible AI practices
• Knowledge of distributed systems or event-driven architecture

More skills:

Large language models (LLMs), Backend engineering, Scalable service architectures, LLM APIs, Vector search, Retrieval-augmented generation (RAG), Prompt engineering, Model Context Protocol (MCP), AI governance principles, Autonomous decision workflows, System design, Performance optimization

Other:

• Full time job schedule
• Short Term Incentive available
• Work arrangement is hybrid
• Division: Underwriting Solutions
• Verisk Analytics is an equal opportunity employer
• Verisk has been recognized as a Great Place to Work in multiple countries
• Verisk values a people-first culture fostering innovation, collaboration, and belonging
• Verisk has received awards from The Wall Street Journal and Forbes for workplace culture and management
• Verisk has a minimum hiring age of 18 except where local laws require higher
• Unsolicited resumes sent to Verisk become company property and no fee is paid for placements from unsolicited resumes