Sr Consultant, Software Engineer (AI Engineer)

Nationwide Mutual Insurance•Columbus, OH

1d•Hybrid

About The Position

The Sr Consultant, Software Engineer (AI Engineer) turns AI strategy into trusted, reusable technology capabilities that enable Nationwide to build and operate AI Systems at scale. This role connects enterprise technology, business architecture, transformation strategy, and delivery teams to move from experimentation to secure, measurable, repeatable business outcomes. It owns the technology-side AI enablement agenda, including defining the capability roadmap and target state, coordinating shared capability development, ensuring reusable products, patterns, and platforms are built, leading a small engineering pod, and supporting AI skills and ways of working across the organization. The role leads the development and adoption of reusable AI capabilities as products, guiding technology consultants and delivery teams in AI readiness and use of approved patterns and the AI-Assisted Delivery Lifecycle. It partners with business architects, transformation strategists, enterprise AI, architecture, data, cybersecurity, risk, privacy, engineering, product, and business leaders to redesign work and ensure solutions are secure, responsible, scalable, explainable, and aligned with enterprise standards. It establishes practices to move proven concepts from prototype to production and defines measures of success such as adoption, reuse, cycle time, quality, reliability, risk and control performance, capacity released, and realized business value. This position works a hybrid schedule, coming into the Columbus, Ohio (preferred), Des Moines, Iowa, or Scottsdale, Arizona office two days per week. Remote internal associates may also be considered. The position could be filled within any of the lower 48 U.S. states. It reports to a Technology Director or above.

Requirements

Eight or more years of programming, software engineering, or analysis experience.
Significant experience leading technology strategy, product or platform management, software engineering, architecture, or digital transformation in a complex enterprise.
Demonstrated experience delivering practical generative AI, agentic AI, automation, data, or platform capabilities into production.
Strong understanding of cloud, APIs, data and knowledge platforms, modern engineering practices, DevSecOps, observability, and the operating requirements of reliable AI Systems.
Experience establishing reusable standards, reference patterns, governance, and product operating models across multiple delivery teams.
Hands-on technical leadership experience leading project teams and setting technical direction.
Proficiency in multiple programming languages, such as Java, C++, Python, and JavaScript.
Extensive knowledge of the software development lifecycle.
Proven ability to tackle sophisticated business and development problems and thrive in a team environment.
Ability to translate complex technology into clear business outcomes and partner effectively with business architects, transformation leaders, executives, and delivery practitioners.
Experience driving organizational change, technology adoption, and enterprise upskilling through practical coaching and measurable enablement.
Executive presence, strategic judgment, strong written and verbal communication, and ability to influence without relying solely on formal authority.
Undergraduate studies in computer science, management information systems, or a related degree; technology experience or non-traditional technology certificates may substitute for an undergraduate degree.
Regularly and consistently demonstrate Nationwide Values.

Nice To Haves

Experience in a regulated industry.
Insurance or financial services industry knowledge.

Responsibilities

Own the technology AI Enablement strategy, roadmap, outcomes, and investment priorities across AI platforms, architecture, data, integration, security, quality, observability, and operational controls.
Ensure reusable capabilities are available to build and run AI Systems, including reference architectures, golden paths, engineering patterns, toolchains, knowledge-grounding approaches, evaluation methods, monitoring, auditability, and human-oversight controls.
Lead a small engineering pod focused on experimentation, rapid proofs of concept, and reusable AI capability building.
Lead technology consultants who help delivery teams improve AI readiness, adopt approved patterns, and incorporate the AI-Assisted Delivery Lifecycle into daily work.
Lead shared capability development across enterprise technology and partner organizations, clarify centralized and federated responsibilities, and reduce duplicate or one-off solutions.
Manage reusable AI capabilities as products by establishing vision, roadmaps, backlogs, lifecycle ownership, adoption plans, service health measures, and continuous improvement practices.
Partner with business architects and transformation strategists to map current and future states, redesign value streams, identify where AI, automation, and human judgment fit, and sequence transformation horizons.
Partner with enterprise AI, architecture, data, cybersecurity, risk, privacy, engineering, product, and business leaders to ensure solutions are secure, responsible, scalable, explainable, and aligned with enterprise standards.
Establish repeatable intake, prioritization, delivery, quality, and operationalization practices to help teams move proven concepts from prototype to production.
Support upskilling, Enterprise AI Fluency efforts, and change management tactics in support of strategic priorities.
Define and communicate success measures, including adoption, reuse, cycle time, quality, reliability, risk and control performance, capacity released, and business value realized.
Lead and develop the team while influencing through matrixed teams, shared services, strategic partners, and business stakeholders.
Analyze complex solutions; develop, test, debug, document, and deploy software according to standards and best practices.
Apply secure software and systems engineering practices throughout the delivery lifecycle to protect data and technology solutions from threats and vulnerabilities.
Serve as a top technical expert and mentor and train others on design techniques, tools, and coding standards.
Advise on using technology to achieve technology and business goals; drive cross-organizational collaboration on projects and shared technical roadmaps.
Set technical direction for DevSecOps practices, tooling, and techniques across teams to strengthen security, automation, reliability, and delivery speed.
Guide solution design, establish engineering standards, align teams on technical direction, and drive continuous learning and improvement.
Manage multiple complex project priorities, deadlines, and deliverables proactively.
May perform other responsibilities as assigned.

Benefits

Medical, dental, and vision coverage
Life insurance
Short- and long-term disability coverage
Paid time off, with newly hired associates receiving a minimum of 18 days per full calendar year, prorated quarterly based on hire date
Nine paid holidays
Eight hours of Lifetime paid time off
Eight hours of Unity Day paid time off
401(k) with company match
Company-paid pension plan
Business casual attire