Director – Release Train Engineer

Director – Release Train Engineer

Requirements

• 5+ years of IT leadership experience executing large scale programs and change management.
• Proven track record as a results-oriented IT leader that collaborates well with business leaders and manages business outcomes.
• Deep knowledge of technology, software Engineering, and experience in Scaled Agile methodology required.
• Strong understanding of business strategy and aligning technology roadmaps to business.
• Strong people leadership abilities with skills in coaching and mentoring talent.
• Ability to successfully work across all levels of the organization, including interacting with senior management.
• Proven ability to manage complex vendor relationships and experience working with an offshore delivery model.
• Strong analytical, critical thinking and problem solving skills, and thorough attention to detail.
• Proven Leadership through IT Transformations in building, managing and scaling teams to deliver outcomes.

Responsibilities

• Lead large-scale technology transformation programs and solve complex use cases using GCP AI Platform/Vertex AI, AWS Bedrock, and Microsoft Azure CoPilot.
• Manage relationships with Product Managers, AVPs and VPs of IT Management, the Lean Portfolio Manager, and other leaders, ensuring alignment across roadmap planning, prioritization of features, benefit realization, epic status, and key risks.
• Drive agile maturity at the program level, including planning periodic reviews and planning sessions with team and product stakeholders, such as ART Synch, Release Planning, System Demos & Solution Demos, the Inspect & Adapt Workshops, and the Scrum of Scrums.
• Facilitate Program Increment (PI) Planning readiness and the PI Planning Event, optimizing readiness by fostering preparation of Vision, Backlogs, Roadmap, and Ideation processes.
• Collaborate with the appropriate individuals to translate business strategy into technology strategy and ensure that capabilities required by the business are enabled.
• Identify enterprise-level continuous improvement opportunities and drive alignment and implementation.
• Execute on workforce transformation strategies, including vendor resources, to increase productivity and improve technical understanding where necessary to achieve an optimum balance.
• Track and communicate key ART and Engineering metrics consistent with governance standards, using data insights to identify improvement opportunities.
• Assess and mitigate risks (such as bias) in AI-generated outputs.
• Use generative AI tools (for example, Microsoft Copilot integrated in Power BI) to transform raw data into actionable insights.

Preferred Qualifications

No preferred qualifications provided.