Director, Artificial Intelligence Engineering

We are seeking a strategic and hands-on Director, AI Engineering to lead the design, development, and scaling of Generative and Agentic AI systems that transform how our company operates and serves customers. This role focuses on building AI applications and reusable AI platform capabilities powered by large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP), multi-agent systems, Agentic AI platforms, and modern AI/ML infrastructure across the enterprise for both internal and customer-facing use cases.

The ideal candidate combines deep expertise in a modern AI/ML stack with strong AI software engineering fundamentals, strong people leadership, and the ability to partner effectively across technology, data, product, operations, and business teams.

You will help defining the AI engineering strategy and roadmap, lead a high-performing AI Engineering team, build and manage scalable AI products, establish standards for scalable and secure AI delivery, and help translate AI investments into measurable business outcomes.

Key Responsibilities

• Help to define and lead the execution of AI engineering strategy, target architecture, and roadmap for Generative and Agentic AI across the enterprise.
• Manage and motivate a high-performing team of AI engineers including coaching, mentoring, and scaling as required.
• Design, build, and oversee deployment of scalable LLM-powered applications and AI-native products for customer support, business operations, and internal productivity.
• Lead the development of AI agents, agentic platforms, and autonomous workflows capable of reasoning, planning, and executing multi-step tasks.
• Implement RAG architectures and pipelines to leverage proprietary data, internal knowledge bases, enterprise systems, and structured/unstructured content.
• Stand-up and evolve MCP servers, tool integrations, and multi-connectivity AI platforms to support secure orchestration across internal and external systems.
• Establish and oversee standards for prompt design, model evaluation, guardrails, observability, testing, and production readiness to ensure accuracy, resiliency, security, and regulatory compliance.
• Lead the design of MLOps and LLMOps pipelines for model lifecycle management, monitoring, continuous evaluation, and improvement.
• Leverage CI/CD and Agile methodologies for AI product development.
• Partner with architecture, security, legal, compliance, and data teams to ensure AI solutions meet requirements for privacy, governance, auditability, and responsible AI.
• Drive build vs. buy decisions, vendor selection, and collaboration with external partners, consultants, and internal teams to deliver scalable, high-quality AI solutions.
• Work closely with business leaders to identify and prioritize high-value use cases across the insurance business, process optimization, software development, and employee productivity.
• Define and track success metrics for adoption, quality, reliability, business impact, cost efficiency, and delivery velocity.
• Stay current with emerging advancements in AI/ML, Generative AI, agentic frameworks, model architectures, and enterprise AI engineering practices.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or a related field.
  Graduate degrees are preferred, but not necessary.
• 10+ years of experience in software engineering, platform engineering, machine learning, or data science, with 2+ years in AI systems development.
• 5+ years of engineering leadership experience, including leading, mentoring, and scaling high-performing technical or AI/ML teams.
• Proven experience delivering LLM-powered applications and AI/ML systems into production at enterprise scale.
• Deep understanding of AI supporting infrastructure, security, testing, and monitoring/maintenance pipelines.
• Strong knowledge of Python, with hands-on experienc