Blackbaud logo
Blackbaud

Blackbaud is a large, private company founded in 1981 to provide technology solutions to nonprofit organizations. The company helps its clients with fundraising

Principal Security Architect, Enterprise AI Solutions

Location

United States

Posted

31 days ago

Salary

$117.2K - $157.5K / year

Seniority

Lead

Job Description

Principal Security Architect, Enterprise AI Solutions

Blackbaud

Role Description Blackbaud is looking for an experienced AI Security Solution Architect to help drive and securely enable the enterprise's AI strategy. The candidate will focus on embedding security into AI/ML platforms, generative AI use cases (e.g., LLMs), and data pipelines—ensuring that emerging AI capabilities are leveraged responsibly while protecting enterprise and customer data. This role is accountable for translating evolving AI and security trends into practical, differentiated solutions that enhance our security posture and business outcomes. As a member of the Cyber Security team, you will operate in a fast-paced, agile environment and collaborate across architecture, engineering, and business teams to ensure security requirements are integrated into both traditional and AI-enabled solutions. What You Will Be Doing - Collaborate with business and technology partners to prioritize and deliver on the security vision and strategy, with a strong focus on secure AI enablement. - Design secure, scalable, and resilient solutions across AI/ML platforms, generative AI tools, and data ecosystems, proactively identifying integration risks and architectural gaps. - Serve as a subject matter expert in AI security architecture, advising on topics such as model security, prompt injection risks, data leakage, and AI supply chain risks. - Develop and implement security guardrails for enterprise AI usage, including data handling policies, access controls, model governance, and usage monitoring. - Evaluate and assess third-party AI solutions and vendors, ensuring alignment with Blackbaud’s security standards and acceptable risk levels. - Stay current on emerging technologies and threats, especially in AI/ML security, adversarial AI, and LLM vulnerabilities, and translate them into actionable strategies. - Partner with engineering teams to integrate security controls into AI development pipelines (MLOps / LLMOps), including secure model deployment and runtime protections. - Define and communicate current state vs. future state AI security architectures, driving roadmap development to mature enterprise AI security capabilities. - Evangelize secure AI practices across the organization, helping establish a culture of responsible AI development and use. - Contribute to security architecture reviews for AI-enabled initiatives, ensuring risk-based decision making without becoming a delivery bottleneck. - Mentor and guide engineers and architects on secure design patterns for both traditional and AI-driven solutions. Qualifications - 8+ years of experience in Information Technology, including designing and implementing enterprise-scale solutions. - 5+ years of experience in Information Security or Security Architecture. - Demonstrated experience securing cloud platforms (AWS, Azure, GCP) and modern application architectures. - Strong expertise in data protection technologies (CASB, DLP, encryption, key management, tokenization, data discovery, etc.). - Experience designing and securing AI/ML or data-driven systems, including exposure to Generative AI / LLM platforms, MLOps / LLMOps pipelines, and model lifecycle management and governance. - Understanding of AI-specific risks, including prompt injection and data exfiltration, model poisoning and adversarial inputs, training data exposure and privacy risks. - Experience implementing security controls for APIs, microservices, and data pipelines supporting AI workloads. - Proven ability to work across stakeholders and drive consensus on complex architectural decisions. - Strong communication skills with the ability to translate security and AI risks into business-relevant outcomes. Preferred Qualifications - Hands-on experience deploying or securing enterprise AI platforms or copilots. - Familiarity with AI governance frameworks (e.g., NIST AI RMF, ISO AI standards). - Experience with security telemetry, monitoring, and anomaly detection in AI systems. - Knowledge of identity and access patterns for AI services, including service identities and token-based access. - Industry certifications including CISSP, CCSP, CRISC, GIAC, AWS, Azure, or GCP certifications, and/or AI/ML-related certifications. Benefits - Medical, dental, and vision insurance. - Remote-flexible workforce. - Wellness Programs. - 401(k) program with employer match. - Flexible paid time off. - Generous Parental Leave. - Donations for Doers. - Pet insurance, legal and identity protection. - Tuition reimbursement program.

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