Principal Enterprise Security & AI Engineering Architect

Delta Dental of Missouri•Sunset Hills, MO

14h•Remote

About The Position

The Principal Enterprise Security & AI Engineering Architect is the organization's most senior individual contributor responsible for defining the future of software engineering, secure software delivery, Artificial Intelligence (AI)-enabled development, and engineering automation. This role provides enterprise-wide technical leadership across software engineering, architecture, cybersecurity, cloud platforms, and AI engineering disciplines. This role will be responsible for establishing the engineering standards, reference architectures, governance frameworks, modernization strategies, AI engineering practices, and developer productivity capabilities that improve how enterprise software is designed, developed, secured, deployed, and operated. Success in this role will be achieved through technical expertise, organizational influence, innovation, collaboration, mentorship, and thought leadership rather than direct organizational authority. The individual will work closely with executive leadership, enterprise architecture, cybersecurity, infrastructure, and application development teams to guide the evolution of enterprise technology capabilities and practices. This role requires broad expertise spanning software engineering, architecture, cloud technologies, security engineering, DevSecOps, and AI-enabled development practices, along with a demonstrated ability to lead complex enterprise transformation initiatives.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field; Master's degree preferred.
15+ years of progressive experience designing, developing, securing, and modernizing enterprise technology solutions.
Demonstrated success operating as a senior technical leader (e.g., Principal Engineer, Distinguished Engineer, Architect, Director, or equivalent) within a large and complex organization.
Deep expertise across multiple domains of enterprise technology, including software engineering, application architecture, cloud platforms, infrastructure engineering, DevOps/DevSecOps, and platform engineering.
Experience establishing enterprise standards, reference architectures, governance models, and software engineering practices adopted across multiple teams or business units.
Strong understanding of modern software engineering, cloud-native architectures, distributed systems, automation, and developer productivity platforms.
Experience integrating security into software development through secure-by-design principles, DevSecOps practices, application security engineering, and software supply chain security.
Experience implementing or governing AI-assisted software development, AI engineering capabilities, or enterprise AI adoption initiatives.
Demonstrated success leading enterprise technology transformation initiatives and influencing organizational change through technical leadership rather than direct authority.
Exceptional communication, stakeholder management, analytical, and problem-solving skills.

Nice To Haves

Experience in healthcare, insurance, financial services, or another highly regulated industry.
Experience with public cloud platforms such as Azure, AWS, or GCP.
Experience with Kubernetes, platform engineering, and internal developer platforms.
Experience working with distributed, offshore, or vendor-supported teams.
Experience developing AI governance frameworks or enterprise AI engineering strategies.
Professional certifications such as CISSP, TOGAF, Azure Solutions Architect, AWS Solutions Architect, CKA, or equivalent.

Responsibilities

Define and lead the organization's AI-enabled Software Development Life Cycle (AI-SDLC).
Lead strategic enterprise AI engineering transformation initiative that establish and validate standards, automation, governance, and operating models for AI-enabled SDLC.
Develop reusable engineering frameworks, reference architectures, governance models, automation capabilities, and best practices that become the standard for software delivery across the organization.
Establish standards for AI-assisted software development including code generation, intelligent code reviews, automated testing, documentation, developer productivity, and AI-enabled engineering workflows.
Evaluate, implement, and govern enterprise AI engineering platforms, coding assistants, agentic development capabilities, and intelligent developer productivity solutions.
Define responsible AI engineering standards and governance that balance innovation, quality, security, compliance, and operational excellence.
Continuously evaluate emerging AI technologies and integrate them into enterprise engineering practices.
Define enterprise software engineering standards and development methodologies.
Modernize engineering practices across application development teams.
Establish reusable engineering frameworks, development accelerators, and engineering patterns.
Improve software quality through standardized engineering practices, automation, and engineering metrics.
Champion engineering excellence, developer productivity, and continuous improvement across the software development lifecycle.
Define enterprise secure software engineering standards and integrate security throughout every phase of the SDLC.
Establish secure-by-design engineering practices that enable developers to build secure applications by default.
Define standards for: Secure Coding, Threat Modeling, Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST), Software Composition Analysis (SCA), Software Supply Chain Security, Secrets Management, Infrastructure as Code Security, Container and Kubernetes Security, Vulnerability Management.
Partner closely with Cybersecurity to mature the enterprise Application Security Engineering program.
Promote a developer-first security culture that balances speed, productivity, and security.
Define and oversee secure adoption standards for AI-assisted development, including protection of source code, intellectual property, sensitive data, and model governance controls.
Define cloud-native engineering standards and modernization strategies.
Establish engineering standards for scalable, resilient, cloud-first applications.
Drive modernization across: CI/CD Pipelines, Infrastructure as Code, Platform Engineering, Containers & Kubernetes, API Management, Event-Driven Architectures, Observability, Operational Automation.
Develop reusable engineering platforms that accelerate software delivery.
Collaborate with Enterprise Architecture to align engineering practices with enterprise technology strategy.
Define application architecture standards that improve scalability, interoperability, maintainability, resiliency, and performance.
Chair or participate in enterprise architecture review committees and governance processes related to software engineering standards, modernization initiatives, and AI Adoption.
Provide architectural leadership for modernization and digital transformation initiatives.
Bridge Enterprise Architecture, Application Architecture, Software Engineering, Infrastructure Engineering, Platform Engineering, and Cybersecurity disciplines.
Serve as the organization's principal technical authority for AI-enabled software engineering, secure software delivery, and engineering modernization.
Influence engineering strategy across software engineering, architecture, infrastructure, cybersecurity, cloud engineering, platform engineering, and product organizations.
Mentor engineers, architects, security professionals, and technical leaders.
Lead proof-of-concepts and reference implementations for emerging technologies.
Participate directly in architecture reviews, engineering innovation, and complex technical problem solving.
Remain hands-on in software architecture, engineering, automation, prototyping, and AI implementation.