Nationwide's Information Technology team is looking to improve the software development lifecycle (SDLC) through foundational AI capabilities, processes, and tooling.
Requirements
- Foundational understanding of SDLC and AI technologies.
- Awareness of emerging technologies and/or industry trends.
- Delivery leaders should also understand relevant Agile/Lean/DevOps tools and techniques.
- Ability to make decisions and recommendations.
- Aptitude to influence, establish relationships and set priorities.
- Excellent verbal and written communication skills to interact with all levels of associates, senior management and/or vendors.
- Technology certifications or PMI, SAFE, Agile or Lean designations are encouraged.
Responsibilities
- Lead planning, execution tracking, and evaluation of AI/automation prototypes to address SDLC inefficiencies, in collaboration with architecture and engineering teams.
- Define and track success metrics (e.g., productivity, ROI, scalability) and manage value realization across experiments and pilots.
- Align solution development with enterprise architecture, security, compliance, and modernization strategies including key dependency management activities with two adjacent workstreams.
- Responsible for applying secure software and systems engineering practices throughout the delivery lifecycle to ensure our data and technology solutions are protected from threats and vulnerabilities.
- Drives the prioritization of deliverables, manages complex issues/risks, governs dependencies.
- Oversees the delivery of status/health reports to drive value delivery tracking (ex: KPIs), optimizes the flow of value and ensures demand/capacity is managed.
- Manages and consults on complex and/or project/product financials.
Other
- Lead the Foundational AI workstream.
- Coordinate cross-functional teams.
- Manage vendor relationships, including selection, proof-of-concept execution, and contract negotiations in partnership with procurement and legal.
- Communicate outcomes and recommendations to senior leadership to inform scaling decisions.
- Foster a culture of responsible experimentation, ethical AI practices, and continuous learning across the technology organization.
