Senior Principal Software Application Security

Huntington National Bank•Atlanta, GA
•Remote

About The Position

Huntington is seeking a highly experienced Senior Principal Software Application Security professional to lead the design, development, deployment, and operation of enterprise-scale frameworks and AI solutions within its Cybersecurity organization. The role requires deep expertise across the software development lifecycle, including architecture, development, testing, security, DevSecOps, cloud engineering, AI agent development, and production operations. The position will influence and define cybersecurity frameworks across the organization. The successful candidate will be a hands-on senior technologist who designs and develops complex solutions from concept through production while providing technical leadership, mentoring developers, and establishing engineering standards. The work involves modern application development, cloud-native architectures, AI-enabled systems, cybersecurity tool integration, container platforms, CI/CD automation, and secure software engineering. The position is remote.

Requirements

  • Bachelor's degree or at least 4 additional years of equivalent experience in software development and/or cybersecurity.
  • At least 8 years of production support and design of cybersecurity technologies.
  • At least 8 years of operational experience with security technologies.
  • At least 8 years of expertise across the full software development lifecycle, including requirements, architecture, coding, testing, deployment, operations, and lifecycle management.

Nice To Haves

  • Ability to influence frameworks across cybersecurity applications and tools and gain stakeholder buy-in across the organization.
  • At least 10 years of software development experience building enterprise applications, platforms, and services.
  • Experience developing solutions using multiple programming languages, such as Python, Java, C#, JavaScript/TypeScript, Go, SQL, PowerShell, and scripting languages.
  • Demonstrated experience designing and developing RESTful APIs, microservices, and event-driven services for enterprise AI and automation capabilities.
  • Experience with agentic AI, Claude code, copilots, RAG architectures, and LLM orchestration frameworks.
  • Experience implementing AI governance, model risk management, and security guardrails.
  • Ability to build and maintain a centralized AI agent registry that supports agent onboarding, unique agent identification, metadata management, ownership tracking, lifecycle status, versioning, and auditability.
  • Experience developing user interfaces and operational dashboards for monitoring, managing, and supporting AI agents, workflows, system health, and service activity.
  • Experience implementing cybersecurity tools, both hardware and software.
  • Knowledge of data engineering, streaming analytics, and log/telemetry processing.
  • Experience integrating applications with identity and access management platforms, including OAuth 2.0, OIDC, scoped tokens, service principals, managed identities, and role-based access controls.

Responsibilities

  • Design, build, and deploy AI/ML and generative AI applications for cybersecurity operations and enterprise use cases.
  • Serve as a senior technical leader and trusted advisor; mentor engineers and elevate engineering capabilities across teams.
  • Establish development standards, patterns, and best practices; evaluate emerging technologies and drive innovation initiatives.
  • Embed cybersecurity controls, secure coding practices, and data protection measures into AI applications and development pipelines.
  • Develop solutions for threat detection, alert triage, vulnerability analysis, identity analytics, and risk scoring.
  • Implement intelligent automation and agent-driven workflows to optimize cyber operations and reduce manual effort.
  • Engineer pipelines and analytics solutions that process logs, telemetry, and security data to generate actionable insights.
  • Deploy and manage scalable AI solutions in cloud-native environments using Kubernetes, containers, APIs, and CI/CD pipelines.
  • Integrate AI applications with enterprise and cybersecurity tools, including SIEM, SOAR, IAM, and data platforms.
  • Ensure alignment with AI governance, regulatory requirements, and secure SDLC practices.
  • Partner with engineering, cybersecurity, architecture, cloud, infrastructure, data, and AI governance teams.
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