Locations: London | Lisbon

Who We Are

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.

What You'll Do

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 partnering 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
  
  

What You'll Bring

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Cybersecurity, or
  
  

related technical field.

• Strong experience in cybersecurity with demonstrated exposure to AI/ML, cloud, or
  
  

application security.

• 5+ 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.
  
  

Preferred Qualifications

• 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.

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