Principal Security Architect

LPL Financial•Charlotte, TX

9d•Hybrid

About The Position

LPL Financial’s Information Security team is seeking a Principal Security Architect to work on cloud, on-premises, and data security architecture initiatives. The role partners with Development, Operations, business units, and Enterprise Architecture teams to secure and monitor environments. The successful candidate will bring broad technical cloud security expertise, with an emphasis on security design, detection, prevention, and response to threats. The architect will lead security architecture and design, develop reusable security patterns and standards, and help align security initiatives with business objectives and regulatory expectations. The role also covers API security, threat and risk analysis, enterprise security controls, and risk management. Additional responsibilities include designing protections for AI and machine-learning systems, including secure pipelines, model integrity, data privacy, and safeguards against adversarial attacks.

Requirements

At least 3 years of experience in secure architecture designs.
At least 8 years of experience with information security controls, guidelines, and standards, such as the ISO 27000 series, OWASP, CSA CCM, CIS 20 Critical Security Controls, SOX, and NIST.
Self-driven and flexible, with strong consulting, negotiation, communication, consensus-building, and presentation skills.
Ability to remain calm under pressure while managing multiple tasks.
Demonstrated ability to learn from mistakes and apply constructive feedback to improve performance.

Nice To Haves

Bachelor’s degree or equivalent years of experience.
Technical knowledge or coding skills in Java, C# .NET, Ruby, and/or Python.
In-depth knowledge of AWS core services, including EC2, S3, IAM, and VPC, and security services such as security groups, ACLs, AWS Security Hub, AWS WAF, and Amazon GuardDuty.
Working knowledge of Terraform, CloudFormation, Pulumi, and/or Ansible.
Experience securing scalable web architectures and distributed systems.
Understanding of malware, emerging threats, attacks, and vulnerability management.
CCSP or another cloud-specific certification, CISSP, and/or GIAC certification.
AI/ML security experience, including a proven record securing ML models and AI pipelines in financial services.
Proficiency in ML algorithms, deep-learning frameworks, and AI ethics.
Experience with AI/ML security controls.
Expertise in OAuth, OpenID Connect, and JWT.
Proficiency in API threat modeling and automated security testing.

Responsibilities

Secure APIs using access controls, OAuth, JWT, and API gateway security to ensure authenticated and authorized access.
Develop reusable security design patterns for common cybersecurity challenges across technology stacks and business domains.
Create actionable security standards and policies aligned with industry best practices and regulatory requirements, while accounting for emerging technologies.
Lead the design and innovation of security architectures that protect against evolving threats while supporting business agility and growth.
Collaborate with stakeholders to align security initiatives with business objectives and integrate them across the organization.
Apply cybersecurity frameworks and expertise in network security, cloud security, identity management, encryption, zero-trust architectures, and secure DevOps.
Conduct threat modeling, risk assessments, and vulnerability management; support SIEM implementation, log analysis, and incident response in enterprise environments.
Analyze threats using intelligence and analytics to identify and proactively mitigate security risks and reduce business impact.
Implement and oversee a risk management framework that balances security investments with business needs.
Secure machine-learning models against adversarial attacks, protect data privacy in AI training sets, and apply ethical AI principles in security applications.
Develop secure AI/ML pipelines, including model integrity verification, secure feature engineering, and anomaly detection in AI-driven systems.