Cybersecurity Risk Engineer Jobs in Milwaukee, WI

As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.

Recruiting for this role ends on 9/19/2026.

Work you'll do

You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.

Key Responsibilities

Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.

Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.

AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.

Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.

Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.

Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.

Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.

Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.

Impact

This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.

The successful candidate would possess these skills

• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to mentor and provide clear guidance to others

The team

Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The ~3,000 professionals in DT - US deliver services including:

• Cyber Security
• Technology Support
• Technology & Infrastructure
• Applications
• Relationship Management
• Strategy & Communications
• Project Management
• Financials

Cyber Security

Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.

Areas of focus include:

• Risk & Compliance
• Identity & Access Management
• Data Protection
• Cyber Design
• Incident Response
• Security Architecture
• Business Partnership

Qualifications

Required:

• Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration

• Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
• Minimum 1 year of people and/or process management experience

Preferred:

• Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
• Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
• Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
• Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
• Knowledge of data protection, identity/access management, and secure architecture patterns
• Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
• Strong communication skills with the ability to translate technical concepts into business-relevant insights

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118,700 to $243,700.  

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance. 

EA_ExpHire
RITM10427821

As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.

Recruiting for this role ends on 9/19/2026.

Work you'll do

You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.

Key Responsibilities

Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.

Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.

AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.

Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.

Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.

Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.

Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.

Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.

Impact

This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.

The successful candidate would possess these skills

• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to mentor and provide clear guidance to others

The team

Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The ~3,000 professionals in DT - US deliver services including:

• Cyber Security
• Technology Support
• Technology & Infrastructure
• Applications
• Relationship Management
• Strategy & Communications
• Project Management
• Financials

Cyber Security

Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.

Areas of focus include:

• Risk & Compliance
• Identity & Access Management
• Data Protection
• Cyber Design
• Incident Response
• Security Architecture
• Business Partnership

Qualifications

Required:

• Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration

• Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
• Minimum 1 year of people and/or process management experience

Preferred:

• Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
• Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
• Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
• Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
• Knowledge of data protection, identity/access management, and secure architecture patterns
• Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
• Strong communication skills with the ability to translate technical concepts into business-relevant insights

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. A...