Security Engineer, AI & Cloud Platform (m/f/d)

Bain & Company; Greater London; On-site; GBP 120,000 - 190,000; Full time

Job summary

Bain & Company, Inc. in London seeks a Lead Staff Security Engineer to own the security posture of the Growth AI Performance System. You will secure cloud infrastructure, API surfaces, and AI workflows while embedding security into development and delivery.

You will guide threat modeling, incident response, and compliance activities, working with cross‑functional teams to protect client data and enable secure innovation at scale.

Qualifications

• Minimum 5 years hands-on cybersecurity or cloud security experience.
• Experience securing Azure/AWS cloud environments and IAM, secrets management, monitoring.
• Experience owning security controls for cloud-native apps.
• Strong understanding of RBAC, OAuth 2.0, token validation, and least-privilege.
• Knowledge of AI security risks and mitigation strategies.
• Ability to model threats and embed security into DevSecOps.
• Familiar with GDPR, SOC 2, and enterprise data security requirements.
• Able to communicate security concepts to technical and nontechnical audiences.

Responsibilities

• Secure and harden cloud infrastructure across Azure or AWS.
• Design and maintain authentication, authorization, and identity controls.
• Own secrets management, rotation, and secure configurations.
• Collaborate with DevOps to embed security into CI/CD pipelines.
• Design safeguards for AI-powered workflows and RAG pipelines.
• Lead threat modeling and security reviews for features and changes.
• Support client compliance reviews and security documentation.

Skills

Cybersecurity

Azure/AWS security

Cloud-native security

IAM/OAuth

AI security

Threat modeling

DevSecOps

Regulatory compliance

Stakeholder communication

Education alignment

Education

Associate's or Bachelor's in CS/Engineering/Math

Tools

Garak

PyRIT

Job description

Staff Security Engineer, Platform Advisory (m/f/d)

Job ID

111448

Work Areas

Technology & Engineering

Employment Type

Permanent Full-Time

Location(s)

London

Description & Requirements

What Makes Us a Great Place to Work

We are proud to be consistently recognized as one of the world’s best places to work. We are currently the top ranked consulting firm on Glassdoor’s Best Places to Work list and have earned the #1 overall spot a record seven times. Extraordinary teams are at the heart of our business strategy, but these don’t happen by chance. They require intentional focus on bringing together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive work environment. We hire people with exceptional talent and create an environment in which every individual can thrive professionally and personally.

Who You'll Work With

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.

You’ll have the opportunity to shape security architecture and engineering practices from an early stage, with the support and global reach of Bain. As our platform evolves through real‑world client engagement, your work will directly influence how we protect enterprise data, secure AI‑powered workflows, and deliver trusted solutions at scale.

Where You’ll Fit Within the Team

As a Lead Security Engineer, you’ll take ownership of the security posture of Bain’s Growth AI Performance System, spanning cloud infrastructure, APIs, agentic AI workflows, data pipelines, and knowledge systems.

This is a hands‑on engineering role where you’ll embed security into the development lifecycle, strengthen infrastructure, conduct threat modeling and security testing, and lead responses to emerging threats.

You’ll play a critical role in securing AI‑powered systems against risks such as prompt injection, data poisoning, unauthorized access, and sensitive data exposure.

Working closely with engineering teams and client stakeholders, you’ll help ensure our platform meets enterprise security expectations while enabling rapid innovation.

What You’ll Do

• 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.

AI & Agentic Security

• 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.

Threat Management, Compliance & Client Engagement

• 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.

About You

Required Qualifications

• 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.

Additional Experience We Value

• 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.

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.