Sr Product Security Engineer, AI & DevSecOps

McKesson•Columbus, OH

About The Position

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to help embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. In this role, you will partner closely with engineering, platform, architecture, and product teams to design secure solutions, automate security controls, and strengthen the security posture of applications and AI systems. You will serve as a security subject matter expert for modern application architectures, machine learning platforms, generative AI solutions, CI/CD pipelines, and cloud infrastructure. This position is ideal for a security professional who enjoys combining hands-on technical expertise, automation, and secure engineering practices to help teams deliver secure, compliant, and resilient products at scale.

Requirements

Degree in Computer Science, Information Security, Engineering, or related technical field, or equivalent experience
Typically requires 7+ years of relevant experience in application security, product security, security engineering, or a related cybersecurity discipline
Experience conducting security architecture reviews, threat modeling, secure design reviews, and vulnerability remediation
Experience implementing DevSecOps practices and integrating security controls into CI/CD pipelines
Experience securing AI/ML platforms, generative AI solutions, large language model applications, or data science workflows
Experience with secure software development lifecycle practices, vulnerability management, and Agile development methodologies
Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform and cloud-native technologies including containers and Kubernetes
Experience with infrastructure-as-code and CI/CD technologies such as Terraform, GitHub Actions, Azure DevOps, GitLab, Jenkins, or similar tools
Proficiency in scripting and automation using Python, PowerShell, Bash, or comparable languages
Experience with security tooling including SAST, DAST, software composition analysis (SCA), container security, secrets detection, and infrastructure scanning

Nice To Haves

Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework
Experience implementing policy-as-code, compliance-as-code, or security automation solutions
Experience supporting regulatory and control frameworks such as SOC 2, HIPAA, SOX, NIST Cybersecurity Framework (CSF), or ISO 27001
Experience with Security Orchestration, Automation, and Response (SOAR) platforms
Ability to communicate complex technical risks and tradeoffs to both technical and non-technical stakeholders
Ability to influence across teams, contribute to technical standards, and promote secure engineering practices

Responsibilities

Conduct security architecture reviews, threat modeling, and security assessments for applications, APIs, cloud services, and AI-enabled systems
Define and implement security requirements, standards, reusable design patterns, and security guardrails across the software development lifecycle
Identify, assess, and help mitigate security risks while partnering with engineering teams to remediate vulnerabilities and strengthen secure coding practices
Assess and secure AI, machine learning, and generative AI solutions, including controls for model governance, secure access, data protection, and AI risk management
Design and implement security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments
Integrate security controls and automated testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning
Develop security automation using scripting, infrastructure-as-code, policy-as-code, and compliance-as-code technologies
Support identity and access management, secrets management, cloud security monitoring, vulnerability management, and incident response activities
Contribute to compliance initiatives, security metrics, risk reporting, and continuous improvement efforts
Provide technical guidance on secure development practices and champion a security-first engineering culture