Your Team and Role:

Blackstone’s Security Engineering (SecEng) Team is responsible for enabling secure software delivery across the firm by identifying, assessing, and reducing technology risk while maintaining development velocity. As Blackstone rapidly expands its use of AI, LLM, machine learning platforms, and AI-enabled software, the SecEng team plays a critical role in ensuring these systems are designed, built, and operated securely.

The Security Engineer – AI & Software Security role focuses on securing AI systems, platforms, and use cases across the firm. This includes working closely with engineering, data science, platform, and product teams to embed security into the AI software development lifecycle, from design through deployment and operation.

This role is highly cross-functional and execution-oriented. You will perform security reviews, threat modeling, code review, penetration testing, and secure design for AI-enabled applications and supporting platforms. You will also help define scalable security patterns and controls that allow teams to safely build and deploy AI solutions in cloud-native environments.

You will join a collaborative team of security and software engineers responsible for evolving how Blackstone approaches application, cloud, and AI security as the firm continues to modernize its technology stack.

Responsibilities:

• Serve as a security engineering partner for AI-enabled applications, machine learning platforms, and data-driven systems across Blackstone.

• Perform architecture and design reviews for AI systems, including model pipelines, inference services, data flows, and supporting cloud infrastructure.

• Conduct secure code reviews for software and services that integrate AI//LLM/ML capabilities, with a focus on identifying security flaws, misuse cases, and unsafe patterns.

• Lead and execute penetration testing and adversarial testing activities for AI-enabled applications and APIs, including abuse scenarios unique to AI systems.

• Develop and maintain threat models for AI systems, addressing risks such as data poisoning, model theft, prompt injection, insecure model deployment, and unauthorized access.

• Partner with engineering and data science teams to embed secure-by-design principles into AI development workflows, CI/CD pipelines, and platform services. • Help define and standardize security controls, guardrails, and reference architectures for applied AI use cases in cloud-native environments.

• Work with platform and cloud teams to ensure AI workloads are securely deployed using containers, Kubernetes, and managed cloud services.

• Translate complex AI security risks into clear, actionable guidance for technical and non-technical stakeholders.

• Contribute to security risk reduction initiatives by identifying systemic AI and application security issues and driving remediation at scale.

• Assist with security incident response and investigations related to AI-enabled systems, including post-incident reviews and control improvements.

• Mentor and support junior engineers, helping grow security engineering capabilities across the team.

• Stay current with emerging AI security threats, industry best practices, and regulatory considerations, applying them pragmatically within the enterprise.

Qualifications:

• A minimum of 6 years of progressive experience in one or more of the following:

  • Software engineering or security engineering, with strong proficiency in languages such as Python, Java, Go, or similar

  • Performing security reviews, code reviews, and design assessments for complex software systems

  • Designing and building resilient, well-documented systems that reduce operational and security risk

  • Working closely with application, platform, DevOps, and infrastructure teams to integrate security into development lifecycles • Managing day-to-day security engineering execution, including handling requests, reviews, and remediation guidance

  • Application security and cloud security, including identification and mitigation of software and infrastructure risks Cloud-native architectures, with a strong preference for AWS, containers, and Kubernetes

  • Infrastructure-as-code (IaC), with hands-on experience using Terraform • Communicating security risks and mitigation strategies effectively to non-security stakeholders

• A minimum of 2 year of experience in one or more of the following areas:

  • Securing AI/ML platforms, pipelines, or AI-enabled applications

  • Threat modeling or risk assessment for data-driven or model-based systems

  • Multi-cloud architecture and security integration

• A minimum of Bachelor’s degree (or foreign equivalent) in Computer Science, Cybersecurity, Engineering, or a related field

The duties and responsibilities described here are not exhaustive and additional assignments, duties, or responsibilities may be required of this position.  Assignments, duties, and responsibilities may be changed at any time, with or without notice, by Blackstone in its sole discretion.

Expected annual base salary range:

Actual base salary within that range will be determined by several components including but not limited to the individual's experience, skills, qualifications and job location. For roles located outside of the US, please disregard the posted salary bands as these roles will follow a separate compensation process based on local market comparables.

Additional compensation and benefits offered in connection with the roleconsist of comprehensive health benefits, including but not limited to medical, dental, vision, and FSA benefits; paid time off; life insurance; 401(k) plan; and discretionary bonuses. Certain employees may also be eligible for equity and other incentive compensation at Blackstone’s sole discretion.