AI Platform Engineer - DevSecOps & Cloud Lead

Nationwide; Columbus (OH); Hybrid; USD 118,000 - 222,000; Full time

Job summary

Nationwide's Technology team seeks a Consultant, Software Engineering — Forward Deployed Engineering to design, develop, integrate, deploy, and support AI-enabled capabilities such as the AI Portal, Model Catalog, and LLM-as-a-Service across the enterprise.

The role collaborates with AI Platform Engineering to extend shared capabilities, ensuring production readiness, reliability, security, privacy, observability, and cost management while driving reuse and enterprise adoption.

Qualifications

• Six or more years of programming, software engineering or systems analysis experience.
• Three years of experience in project management preferred.
• Proficiency in one or more programming languages such as Java, C++, Python, and JavaScript.

Responsibilities

• Apply secure software and systems engineering practices throughout the delivery lifecycle to protect data and technology.
• Mentor and train team members on design techniques, tools, and coding standards.
• Provide strategic technical advice on using technology to achieve business and technology goals/strategy.
• Drive cross-collaboration and execution of projects across multiple teams.
• Analyze solutions, develop, test, debug, document, and deploy moderately complex software according to standards and best practices.
• Champion the adoption and effective use of DevSecOps practices, tooling, and techniques to improve software quality, security, automation, and delivery efficiency across teams.
• Manages multiple medium to large project priorities, deadlines, and deliverables proactively.

Skills

Java

C++

Python

JavaScript

Education

Undergraduate studies in computer science, MIS, mathematics, or related field

Job description

Nationwide's Technology team seeks a Consultant, Software Engineering — Forward Deployed Engineering to design, develop, integrate, deploy, and support AI-enabled capabilities such as the AI Portal, Model Catalog, and LLM-as-a-Service across the enterprise.

The role collaborates with AI Platform Engineering to extend shared capabilities, ensuring production readiness, reliability, security, privacy, observability, and cost management while driving reuse and enterprise adoption.