We are looking for a hands-on Lead AI Engineer with Node.js and TypeScript expertise to help develop an AI-powered Risk Map solution. Working closely with the Solution Architect and an engineering team, you will create an AI-enabled risk assessment system, helping decrease manual effort required from ~30 hours down to ~8 hours per assessment. The scope of the project will require advanced AI-enabled engineering techniques (i.e., spec-driven development) and modern tools (Claude Code, Codex, etc.) to deliver on time and within budget. This role is ideal for an engineer who has experience with real production delivery with AI tools and enjoys working with LLMs, Prompt Engineering, and enterprise AI applications.

Responsibilities

Lead the team of 3-4 engineers in building the system according to architecture and scope defined in Discovery phase Improve prompt quality, AI workflows, and overall solution performance Improve the accuracy, consistency, and reliability of AI-generated outputs Implement new AI capabilities following the solution architecture Support the integration of AI capabilities into the existing platform Collaborate closely with the AI Architect and Lead Engineer Participate in testing, validation, and continuous improvement of AI solutions Troubleshoot AI-related issues and recommend improvements Document implementation details and technical recommendations Requirements 5+ years of experience as an AI Engineer or Software Engineer working with AI solutions Proficiency in Node.js and TypeScript Expertise in LLM and Generative AI Practical experience with Prompt Engineering Experience working with Claude or similar enterprise LLM platforms Familiarity with Claude Skills or similar reusable AI capability frameworks Understanding of AI evaluation, prompt optimization, and AI quality improvement Strong analytical and problem-solving skills Good communication and collaboration skills Proficiency in English at a B2+ level Nice to have Skills in Python Experience with AWS cloud services and Amazon Bedrock Experience integrating AI solutions into enterprise applications Experience with AI guardrails, structured outputs, and evaluation techniques Background in insurance, risk management, financial services, or enterprise automation