Security engineer for AI platforms

You'll join the team building Bain's Growth AI Performance System, an integrated suite of AI-powered decision-making tools that helps large organizations make smarter commercial decisions. Our team combines the analytical depth and client relationships of a leading consultancy with the technical ambition and pace of a product company. You'll work alongside AI engineers, platform engineers, DevOps specialists, and product teams to build secure, scalable solutions that help clients determine where to invest, where to focus, and how to win.

• Secure and harden cloud infrastructure across Azure or AWS, including networking, containers, APIs, storage, and data services.
• Design and maintain authentication, authorization, identity management, and least-privilege access controls.
• Own secrets management, certificate rotation, secure configuration standards, and security monitoring.
• Partner with DevOps engineers to embed security controls into infrastructure-as-code, deployment pipelines, and production environments.
• Design and implement safeguards against AI-specific threats, including prompt injection, jailbreaking, data poisoning, model exfiltration, and agentic workflow exploitation.
• Secure retrieval-augmented generation (RAG) pipelines, vector stores, agent memory systems, and tool integrations.
• Conduct structured security testing and red teaming of AI-powered workflows to identify vulnerabilities and implement effective defenses.
• Develop monitoring and detection capabilities for suspicious AI activity, unauthorized access, and workflow misuse.
• Define AI-specific security incidents and lead incident response activities when needed.
• Lead threat modeling and security reviews for new platform features, integrations, and architectural changes.
• Embed security requirements, automated testing, and review processes into agile engineering workflows.
• Support compliance with applicable GDPR obligations and SOC 2 controls.
• Maintain security documentation and evidence to support client due diligence and compliance reviews.
• Communicate security risks, controls, and incident response procedures to client security teams and senior stakeholders.
• Stay current with emerging AI security threats, frameworks, and tools, sharing knowledge and best practices across the engineering team.

• At least 5 years of hands-on experience in cybersecurity, cloud security engineering, or related roles securing production systems.
• Strong experience securing Azure or AWS cloud environments, including infrastructure, networking, identity and access management, secrets management, and monitoring.
• Demonstrated experience owning security controls and practices for cloud-native applications, including threat modeling, vulnerability remediation, and incident response.
• Strong understanding of authentication and authorization, including role-based access control, OAuth 2.0, token validation, and least-privilege principles.
• Understanding of AI security risks, including prompt injection, data poisoning, sensitive data leakage, and vulnerabilities in AI-powered applications.
• Experience with structured threat modeling methodologies and security testing.
• Experience integrating security practices into DevSecOps workflows and continuous integration and deployment pipelines.
• Working knowledge of GDPR, SOC 2, and enterprise data security requirements.
• Ability to collaborate effectively with cross-functional engineering teams and communicate security considerations to technical and nontechnical stakeholders.
• An associate's or bachelor's degree in computer science, engineering, mathematics, or a related technical field, or an equivalent combination of education, training, and experience.
• Будет плюсом: Experience securing large language model applications, retrieval-augmented generation pipelines, or agentic AI systems; Familiarity with AI security frameworks such as OWASP Top 10 for LLM Applications and MITRE ATLAS; Experience using AI security testing tools such as Garak, PyRIT, or equivalent solutions; Experience supporting enterprise client security reviews and compliance audits; Experience working in agile product engineering or consulting environments; Active use of AI-assisted development tools and a commitment to continuously developing AI security expertise

• Compensation for this role includes base salary, annual discretionary performance bonus, 401(k) plan with an annual employer contribution based on years of service and Bain’s best in class benefits package (details listed below).
• In Massachusetts, the good-faith, reasonable annualized full-time salary range for this role is between 127k and 153k.
• In Illinois, the good-faith, reasonable annualized full-time salary range for this role is between 121k and 146k.
• Placement within these ranges will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level.
• Annual discretionary performance bonus.
• This role may also be eligible for other elements of discretionary compensation.
• 4.5% 401(k) company contribution, which increases after 3 years of service and is 100% vested upon start date.
• Bain & Company's comprehensive benefits and wellness program is designed to help employees achieve personal independence, protection and stability in the areas most important to you and your family.
• Bain pays 100% individual employee premiums for medical, dental and vision programs, offering one of the most comprehensive medical plans for employees without impacting your paycheck.
• Generous paid time off, including parental leave, sick leave and paid holidays.
• Fully vested 401(k) company contribution.
• Paid Life and Long-Term Disability insurance.
• For all other locations, the good-faith, reasonable annualized full-time salary range for this role is commensurate with competitive geographic market rates for this role and will vary based on several factors including, but not limited to experience, education, licensure/certifications, training and skill level.