Director, AI Engineering & Delivery

Excited to grow your career? We value our talented employees and instill an environment where you feel engaged, satisfied and able to contribute your unique skills and talents while living and working as your authentic self. We provide extensive opportunities for personal and professional development, building employee competence and organisational capability to fuel exceptional performance through an inclusive environment both now and in the future.

Our people make all the difference in our success.

In this role, you will lead the execution, operationalisation, scaling, and continuous improvement of enterprise AI engineering and delivery initiatives across Vizient. You will implement scalable AI engineering practices, AI delivery operating models, AIOps and LLMOps capabilities, and cross‑functional engineering standards that enable the organisation to rapidly and responsibly deliver AI‑powered business outcomes, operational efficiencies, and scalable enterprise value. You will partner closely with business, technology, governance, automation, architecture, and quality engineering teams to build production‑grade AI applications, agentic workflows, reusable platform capabilities, and operational processes that support Vizient’s enterprise AI transformation strategy.

• Lead the execution and delivery of enterprise AI engineering initiatives, including AI‑powered applications, LLM‑enabled workflows, agentic orchestration solutions, AI‑enabled automation capabilities, and platform integrations.
• Drive day‑to‑day engineering delivery activities across AI teams, including sprint execution, backlog management, delivery tracking, issue resolution, dependency management, and operational execution.
• Implement and ope rationalise enterprise AI engineering practices, including AI software development lifecycle (SDLC) processes, deployment standards, runtime observability, release management, and engineering quality practices.
• Provide technical oversight across solution design, development, validation, deployment, monitoring, optimisation, and production support activities.
• Support AIOps and LLMOps operational practices, including runtime monitoring, drift detection, observability, incident management, prompt lifecycle management, evaluation execution, operational telemetry, and production reliability.
• Develop reusable AI engineering patterns, implementation playbooks, shared services, templates, internal libraries, and engineering accelerators to improve delivery consistency, scalability, and operational efficiency.
• Drive adoption of enterprise engineering standards, scalable delivery practices, and shared implementation patterns across AI delivery teams.
• Partner with AI Governance, Quality Engineering, Automation, Architecture, and AI Delivery Lifecycle teams to ope rationalise governance requirements, validation processes, responsible AI controls, runtime safeguards, and secure delivery practices.
• Coordinate AI delivery activities across teams, including operational planning, resource management, contractor and vendor alignment, knowledge transfer, and delivery continuity.
• Partner with cross‑functional stakeholders to support technical feasibility assessments, delivery readiness activities, implementation planning, and engineering sustainability efforts.
• Support vendor evaluations, platform implementation initiatives, build‑versus‑buy assessments, and engineering modernisation efforts.
• Lead, mentor, and develop engineering managers, architects, engineers, and contractor teams while fostering a high‑performing, collaborative, and continuously learning culture.
• Communicate delivery progress, operational risks, technical updates, engineering trade‑offs, and implementation recommendations to technical and business leaders.
• Research and evaluate emerging AI engineering, automation, observability, orchestration, and platform technologies to support innovation and continuous improvement.

• Relevant degree preferred.
• 7 or more years of experience in software engineering, AI application engineering, engineering delivery, platform engineering, or enterprise technology functions required.
• 3 or more…