At a Glance
- Tasks: Lead secure design of AI/ML systems and collaborate across teams.
- Company: Join Boston Consulting Group, a pioneer in business strategy and transformation.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Make a real impact in cybersecurity while working with cutting-edge AI technologies.
- Qualifications: Degree in Computer Science or related field; strong cybersecurity and AI/ML experience required.
The predicted salary is between 80000 - 100000 β¬ per year.
Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation - inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive.
We are seeking a highly skilled and technically hands-on Cybersecurity Manager AI Architecture to lead the secure design and engineering assurance of AI/ML systems across the enterprise. This role operates as a technical leader and partners with multiple teams across business units including data science, ML engineering, cloud/platform engineering, application development, security operations, and risk/compliance to embed secure-by-design principles into AI systems. The ideal candidate brings a strong engineering foundation and thrives on hands-on technical execution, architectural ownership, and cross-functional collaboration. They combine deep technical expertise with the ability to influence stakeholders and enable secure, scalable AI adoption across the enterprise.
Key Responsibilities- Lead the design and implementation of secure AI/ML architecture frameworks aligned with zero-trust principles.
- Develop enterprise security standards and reference architectures for LLMs, generative AI platforms, and ML pipelines.
- Conduct AI-specific threat modeling (model poisoning, adversarial attacks, prompt injection, data leakage, model inversion, supply chain risk).
- Embed security controls into AI CI/CD pipelines, MLOps workflows, and DevSecOps processes across business units.
- Ensure secure handling of training data, fine-tuning datasets, model artifacts, and embeddings through encryption and access governance.
- Secure AI workloads in cloud and hybrid environments (AWS, Azure, GCP), including containerized and Kubernetes-based deployments.
- Integrate AI systems with enterprise identity and access management, cloud security posture controls, application security scanning, runtime monitoring, and vulnerability management platforms.
- Define AI-specific logging, telemetry, detection strategies, and incident response readiness.
- Provide hands-on architectural guidance and code-level review when required.
- Bachelors or Masters degree in Computer Science, Engineering, Cybersecurity, or related technical field.
- Strong experience in cybersecurity with demonstrated exposure to AI/ML, cloud, or application security.
- 6+ years of hands-on engineering experience (software engineering, cloud engineering/SRE, systems architecture, ML engineering, or DevOps).
- Strong understanding of AI/ML architectures and MLOps frameworks.
- Experience with threat modeling methodologies.
- Proficiency in Python and secure coding practices.
- Experience working within enterprise environments that include identity management, cloud posture controls, application security scanning, runtime monitoring, and vulnerability management tools.
- Experience securing cloud-native platforms and containerized workloads.
- A technical manager and enterprise security architect.
- Experience implementing NIST AI Risk Management Framework.
- Knowledge of AI governance and emerging AI regulatory compliance requirements.
- Experience with model monitoring, drift detection, AI observability, or adversarial ML testing.
- Hands-on experience with Kubernetes security, Infrastructure-as-Code security, and CI/CD security automation.
- Experience driving cross-business-unit security initiatives.
Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E-Verify Employer.
Cybersecurity Manager - AI Architecture - London employer: Boston Consulting Group
At Boston Consulting Group, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation. Our London office is a hub for diverse talent, providing ample opportunities for professional growth and development in the rapidly evolving field of cybersecurity and AI architecture. With a commitment to employee well-being and a focus on meaningful work, BCG empowers its team members to make a significant impact while enjoying a supportive and inclusive environment.
StudySmarter Expert Adviceπ€«
We think this is how you could land Cybersecurity Manager - AI Architecture - London
β¨Tip Number 1
Network like a pro! Reach out to folks in the cybersecurity and AI fields on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
β¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI/ML security. This gives potential employers a taste of what you can do beyond the application.
β¨Tip Number 3
Prepare for interviews by brushing up on common cybersecurity scenarios and AI-specific challenges. Practising your responses will help you feel more confident and ready to impress.
β¨Tip Number 4
Don't forget to apply through our website! Itβs the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Cybersecurity Manager - AI Architecture - London
Some tips for your application π«‘
Tailor Your CV:Make sure your CV is tailored to the Cybersecurity Manager role. Highlight your experience with AI/ML, cloud security, and any hands-on engineering work you've done. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about cybersecurity and AI architecture. Share specific examples of your past work that demonstrate your expertise and how you can contribute to our team.
Showcase Your Technical Skills:Donβt forget to highlight your technical skills in your application. Mention your proficiency in Python, experience with threat modeling, and any relevant frameworks you've worked with. We love seeing candidates who can back up their claims with solid experience!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. Itβs the easiest way for us to keep track of your application and ensure it reaches the right people. Plus, it shows youβre serious about joining our team!
How to prepare for a job interview at Boston Consulting Group
β¨Know Your Stuff
Make sure you brush up on your technical knowledge, especially around AI/ML architectures and cybersecurity principles. Be ready to discuss specific frameworks and methodologies you've used in the past, as well as any hands-on experience with tools like Kubernetes or cloud security.
β¨Showcase Your Collaboration Skills
This role requires working across multiple teams, so be prepared to share examples of how you've successfully collaborated with data scientists, engineers, and other stakeholders. Highlight your ability to influence and drive security initiatives in a cross-functional environment.
β¨Prepare for Scenario Questions
Expect to face scenario-based questions that test your problem-solving skills in real-world situations. Think about potential threats to AI systems and how you would address them, such as model poisoning or data leakage. Having concrete examples will help you stand out.
β¨Ask Insightful Questions
At the end of the interview, donβt forget to ask thoughtful questions about the company's approach to AI security and their future plans. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals.