Director, Applied AI & Agentic Solutions

What You ll Do for Us

• Lead the delivery and adoption of AI engineering capabilities across a portfolio of digital products, ensuring solutions are scalable, secure, resilient, and aligned to business priorities.

• Manage and develop AI engineering teams, providing coaching, technical direction, performance leadership, and career development.

• Partner with Product Managers, Technical Leads, Data Scientists, and Product Engineering leaders to prioritize and deliver high-value AI solutions.

• Translate enterprise AI strategy, architecture standards, and platform capabilities into actionable delivery roadmaps and implementation plans.

• Provide technical leadership on complex AI initiatives, including model architectures, agent workflows, retrieval strategies, evaluation approaches, and production deployment decisions.

• Drive adoption of enterprise AI standards, reusable patterns, development tools, and engineering best practices across product teams.

• Lead the design, development, deployment, and operation of production AI applications, LLM-powered products, and agent-based solutions.

• Ensure effective implementation of MLOps, LLMOps, and Agent Ops practices, including lifecycle management, deployment automation, observability, monitoring, and operational governance.

• Establish engineering quality standards through architecture reviews, code reviews, testing practices, and operational readiness assessments.

• Partner with Core Technology teams to leverage enterprise AI platforms, orchestration services, and foundational capabilities while identifying opportunities for enhancement.

• Ensure AI solutions comply with enterprise governance, security, responsible AI, privacy, and risk management requirements.

• Drive AI observability and operational excellence through monitoring, evaluation, performance optimization, and continuous improvement practices.

• Support the delivery of enterprise digital twin, forecasting, simulation, optimization, and intelligent automation capabilities.

• Evaluate emerging AI technologies and engineering approaches and recommend opportunities that improve delivery effectiveness and business impact.

• Foster a culture of experimentation, learning, collaboration, and engineering excellence across AI engineering teams.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or a related technical discipline.

• 8+ years of experience in software engineering, AI engineering, machine learning engineering, platform engineering, or related technical disciplines.

• 5+ years of experience leading engineering teams, technical leads, or specialized engineering functions.

• Demonstrated experience delivering production AI solutions, including generative AI, large language model applications, intelligent agents, and machine learning systems.

• Experience leading delivery across multiple products or business domains in a matrixed environment.

• Strong expertise in agentic AI architectures, Retrieval-Augmented Generation (RAG), GraphRAG, semantic search, vector databases, knowledge graphs, and AI orchestration frameworks.

• Hands‑on technical expertise in Python and cloud-native application development, with Azure preferred.

• Experience implementing and operating MLOps, LLMOps, and Agent Ops capabilities in production environments.

• Experience establishing engineering standards, reusable frameworks, development accelerators, and operational best practices.

• Knowledge of responsible AI, cybersecurity, privacy requirements, model governance, and enterprise risk controls.

• Strong leadership capabilities with experience coaching engineers, leading technical teams, and driving organizational capability growth.

• Excellent communication,…