Director, AIML Security

Site Name: USA - Texas - Richardson, Durham Blackwell Street, Philadelphia Walnut Street, Upper Providence, Waltham
Posted Date: Jan 29 2025

At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines.

The Cybersecurity organization is a key partner in GSK's efforts to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines.

We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:

• Building a next-generation, metadata- and automation-driven data experience for GSK's scientists, engineers, and decision-makers, increasing productivity and reducing time spent on "data mechanics"

• Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent

• Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time

The Director, AIML Security will work within GSK's AIML Security and Emerging Technology team, interacting directly with stakeholders and technical teams to drive and support the key programs and projects related to Artificial Intelligence (AI) and Machine Learning (ML). AI/ML are critical to the development of new medicines, particularly as we generate increasingly complex, experimental data at scale. Our vision places machine learning at the centre of human genetics and functional genomics. We see AIML with tightly-coupled, experimental feedback loops, playing a pivotal role in understanding genetics and developing the next generation of medicines. This role will be required to be a subject matter expert in delivering security enhancements into existing and new applications, infrastructure and business processes with a specialty in the areas of AI/ML, data security, data integrity, and data democratization. This includes how to embed security requirements and risk decisions into an agile developed product, making decisions expeditiously to ensure timely delivery of a secure outcome.

The Director, AIML Security will be responsible for designing and implementing governance, compliance, and security strategies to safeguard AI/ML platforms, data products, and associated infrastructure. This role will assess and enhance existing DevOps pipelines, AI/ML platforms, and data ecosystems to establish secure, scalable, and compliant AI/ML operations. The Architect will develop reusable security frameworks, standards, and solution blueprints that promote rapid and sustainable security integration into AI/ML workflows. Collaborating with senior stakeholders, the Architect will define architectural strategies, governance frameworks, and compliance protocols to address risks identified during program and project engagements. This includes evaluating and mitigating risks related to AI/ML model development, deployment, and data integrity while ensuring adherence to evolving regulatory and ethical standards. The Architect will also evaluate and contribute to the implementation of emerging security tools and technologies, enabling the enterprise to stay ahead of AI/ML threats and regulatory requirements. This role is pivotal in driving the maturity of AI/ML security and compliance programs, fostering trust, and ensuring responsible and ethical use of AI technologies within the organization.

The role will be responsible for making recommendations into the direction of the Senior Director, AIML Security and Emerging Technology as well as directed business programs and projects. The role will support teams that are dispersed globally and will interface with the technical leadership teams of our various business units as a trusted advisor.

Key Responsibilities:

• Develop and implement AI security governance frameworks aligned with organizational cybersecurity policies and industry best practices (e. g. , NIST AI RMF, ISO/IEC 27001).

• Assess and mitigate risks associated with AI/ML systems, ensuring compliance with security standards and frameworks.

• Collaborate with cross-functional teams to define AI/ML security policies, including model development, deployment, and operational safeguards.

• Establish monitoring and reporting mechanisms for AI model vulnerabilities, breaches, and non-compliance incidents.

• Conduct or coordinate AI security audits, model evaluations, and penetration testing to identify and remediate risks.

• Ensure effective governance over AI supply chains, addressing risks from third-party models, libraries, and tools.

• Oversee governance processes for AI/ML data products, ensuring data integrity, quality, and lineage across the data lifecycle.

• Design and implement data security controls for AI/ML datasets, focusing on privacy, confidentiality, and ethical considerations.

• Lead initiatives to ensure compliance with data regulations, such as GDPR, CCPA, and sector-specific privacy laws.

• Develop guidelines for secure data sharing and collaboration across internal teams and external partners.

• Manage risks related to biased or unrepresentative data that could compromise AI model outputs.

• Provide thought leadership on AI/ML governance trends and emerging risks, advising senior leadership on strategic priorities.

• Lead the design and integration of secure AI/ML solutions into enterprise workflows, aligning with organizational objectives.

• Develop training materials and awareness programs to promote secure and compliant AI/ML practices across the organization.

• Partner with internal and external stakeholders to establish and maintain a culture of security and compliance in AI initiatives.

• Evaluate and recommend tools and technologies for AI/ML governance and compliance management.

• Knowledgeable of latest available tools and products and capable of evaluating off-the-shelf products.

• Mentor other team members in security best practices.

Basic Qualifications:

• Experience in Engineering, IT, Comp Sci, Information Assurance, Cybersecurity, Management

• 10+ years' experience in Information Technology

• 7+ years' experience in Information Security and Risk

• 5+ years of governance, security, risks, and compliance experience

• Experience developing and delivering security requirements into Agile developed projects and work streams with external dependencies.

• Experience working in a continuous integration and continuous delivery model (CI/CD).

• Experience in modern cloud computing and delivery platforms such as Microsoft Azure, Google Cloud or Amazon AWS.

• Experience designing and delivering security requirements to support agile software development processes (Jira/Confluence/Jenkins).

Preferred Qualifications:

• Experience with security.