Head of AI Engineering 1026

Nexus IT Group is seeking a Head of AI Engineering to shape the company’s AI architecture and lead a team of engineers. The role combines hands-on development of AI-powered products with engineering leadership, responsible AI practices, and delivery in partnership with Product and other teams.

Responsibilities:

• Own the company’s system and AI architecture. Design platforms where models, agents, and traditional services work together, and make the calls on speed, cost, and scale
• Lead the design and build of AI-powered features from prototype to production: LLM integrations, document intelligence, retrieval (RAG), and agentic workflows that automate real work across the loan lifecycle
• Make AI coding assistants and agents the default way the team designs, builds, tests, and documents software, and measure whether they’re actually making us faster and better
• Keep the company on the front edge. Test new models, tools, and techniques quickly, share what you learn, and turn the winners into product
• Be the company’s go-to voice on AI, internally and with customers. Help teams outside engineering put AI to work, and explain what it can and can’t do in plain English
• Own model evaluation, monitoring, data privacy, and human-in-the-loop controls. Partner with Compliance on the company’s ISO 42001 AI management system and the expectations of a highly regulated industry
• Lead a team of traditional and AI engineers as a player-coach, and help every engineer level up their AI skills. Set clear goals, give direct feedback, pair on hard problems, and build a team people want to stay on
• Work hand in hand with the VP of Product to turn the roadmap into technical plans, with honest input on feasibility, sequencing, and effort
• Write production code, build prototypes, and lead by example in code reviews and design discussions
• Run the end-to-end development process, from requirements through deployment, with predictable timelines and honest status updates
• Set and enforce standards for code quality, testing, security, and scalability
• Work with customer success, sales, and leadership to understand what customers need, and explain technical tradeoffs in plain English
• Partner with People Operations to hire, develop, and retain strong engineers, including AI and ML specialists, as the team grows. Set performance goals and run regular reviews
• Evaluate AI models, platforms, and development partners, and manage cost, performance, and lock-in risk
• Keep project documentation and time tracking current in Teamwork