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Senior Engineer - AI/ML Security - job 3 of 4

You Lead the Way. We’ve Got Your Back.

With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.

At American Express, you’ll be recognized for your contributions, leadership, and impact—every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong.

Join Team Amex and let's lead the way together.

As part of our diverse tech team, you can architect, code and ship software that makes us an essential part of our customers’ digital lives.  Here, you can work alongside talented engineers in an open, supportive, inclusive environment where your voice is valued, and you make your own decisions on what tech to use to solve challenging problems.  American Express offers a range of opportunities to work with the latest technologies and encourages you to back the broader engineering community through open source.  And because we understand the importance of keeping your skills fresh and relevant, we give you dedicated time to invest in your professional development.  Find your place in technology on #TeamAmex.

How will you make an impact in this role?

Organizational Context: Executes end-to-end information security, IT risk management processes and automated capabilities that promote trustworthy AI practices. Works across many organizations, both internal and external, to meet business needs and compliance goals. Leads cross department initiatives, covering a wide range of business/technical functions.

Focus: Responsible for the development and or delivery of AI/ML security initiatives, projects, or programs that have objectives associated with incorporating AI safety controls, adversarial robustness, and stress testing of AI/ML systems Responsible for designing and implementing processes to understand, measure, and improve the organization’s ability to protect AI/ML models, implement AI safety controls for responsible use of LLM (Large Language Model) applications.

Key Responsibilities

  • Implement secure model development life cycle practices with automated white box and black box assessments for AI/ML models.
  • Deliver and integrate AI robustness, vulnerability, and stress testing capabilities with MLOps ecosystems.
  • Evaluate and assess open-source AI security libraries to build into enterprise AI stress testing and audit capabilities.
  • Implement end-to-end LLM security risk management processes and automated protections.
  • Incorporate machine learning models into diverse application security tooling and processes.
  • Support production deployments of AI/ML safety systems using cloud-native packaging and deployment techniques suchas containers, serverless, CI/CD and APIs.
  • Establish and govern AI/ML and Generative AI application security standards.
  • Provide production support and operations for AI/ML security systems.
  • Manage cloud deployments and automation frameworks in cloud for AI/ML security systems.

Minimum Qualifications

  • Bachelor's Degree in Data Science, Statistics, Computer Science or Software Engineering
  • 3+ years experience with Machine Learning Application Development
  • 3+ years of software engineering experience

Preferred Qualifications

  • Master's Degree - Data Science, Statistics, Computer Science, or Software Engineering 
  • Machine Learning Operation Professional Certifications
  • Strong knowledge of Adversarial Robustness techniques and tools for machine learning 
  • Strong knowledge of AI Risk Management frameworks and Trustworthy AI practices. 
  • Hands-on experience with applying statistics, machine learning algorithms (DNN, NLP), big data, and data science toolkits. Hands-on experience designing, implementing, and operationalizing high performant AI/ML pipelines and writing production code.
  • Hands-on experience with deploying and operationalizing AI/ML models to public cloud environments.
  • Hands-on experience evaluating open-source ML tools, frameworks, and libraries.
  • Hands-on experience with commonly used data science programming languages, packages, and tools.
  • Hands-on experience with MLOps, DevOps, DataOps and API integrations.
  • Hands-on experience with AI workload management.
  • Hands-on experience with Cloud architecture, design, implementation, and operations.
  • Demonstrated peer reviewed journal publications, conference presentations, open-source contributions, or similar activities.

Salary Range: $110,000.00 to $190,000.00 annually + bonus + benefits

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors.

We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:

  • Competitive base salaries 
  • Bonus incentives 
  • 6% Company Match on retirement savings plan 
  • Free financial coaching and financial well-being support 
  • Comprehensive medical, dental, vision, life insurance, and disability benefits 
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need 
  • 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy 
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) 
  • Free and confidential counseling support through our Healthy Minds program 
  • Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including, but not limited to, the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.

We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.

US Job Seekers/Employees - Click here to view the “Know Your Rights” poster and the Pay Transparency Policy Statement.

If the links do not work, please copy and paste the following URLs in a new browser window: https://www.dol.gov/agencies/ofccp/posters to access the three posters.

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.

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$190000K

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What You Should Know About Senior Engineer - AI/ML Security, American Express

At American Express, we are inviting you to take the reins as a Senior Engineer - AI/ML Security in the vibrant city of Phoenix, Arizona! In this role, you will play an invaluable part in enhancing our security measures around AI and machine learning systems. With a focus on developing robust and secure models, you’ll collaborate with diverse teams and lead initiatives that reinforce our commitment to trustworthy AI practices. Picture yourself implementing secure model development practices, integrating cutting-edge AI robustness assessments, and ensuring our AI systems are not just functional but secure. Your creativity and expertise in AI/ML will help establish standards and protocols that guide our organization towards responsible AI usage. The collaborative atmosphere at American Express means your innovative ideas will be heard and valued as you work alongside fellow talented engineers who share your enthusiasm for tech and customer-first solutions. We provide a supportive environment that encourages continuous learning, with dedicated time for your professional development. If you thrive in a place where you can make tangible impacts and be part of an essential part of our customer’s digital lives, then this is where you need to be. Join us and find out how you can lead the way in AI/ML security today!

Frequently Asked Questions (FAQs) for Senior Engineer - AI/ML Security Role at American Express
What are the key responsibilities of a Senior Engineer - AI/ML Security at American Express?

As a Senior Engineer - AI/ML Security at American Express, you will be responsible for leading the development and delivery of AI/ML security projects. This includes implementing secure model development practices, conducting vulnerability assessments, and integrating automated AI security capabilities. Additionally, you'll assess AI security libraries and implement processes to ensure the robustness and safety of AI applications. Your role will be critical in protecting AI models and managing security risks effectively, supporting cross-department initiatives for comprehensive IT risk management.

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What qualifications do I need to become a Senior Engineer - AI/ML Security at American Express?

To qualify for the Senior Engineer - AI/ML Security role at American Express, you should hold a Bachelor's Degree in a tech-related field such as Data Science or Computer Science. Additionally, 3+ years of experience in machine learning application development and software engineering is needed. Preferred candidates may possess a Master's Degree and professional certifications in Machine Learning Operations, along with strong knowledge of AI risk management techniques and experience with deploying AI models in cloud environments.

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What is the work environment like for a Senior Engineer - AI/ML Security at American Express?

At American Express, the work environment for a Senior Engineer - AI/ML Security is dynamic and inclusive. You'll be part of a diverse tech team that values collaboration and innovation. The culture promotes an open dialogue where team members can express ideas and contribute to solving complex challenges in AI/ML security. You'll gain access to the latest technologies and be encouraged to invest time in your professional development, creating a supportive atmosphere that helps you thrive both personally and professionally.

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How does American Express support the professional development of Senior Engineers - AI/ML Security?

American Express is committed to the professional growth of its employees, including those in the Senior Engineer - AI/ML Security role. The company offers dedicated time for continuous learning and development, access to career training opportunities, and encourages participation in open-source projects. This support ensures that you can stay ahead in the rapidly evolving AI/ML landscape and continue enhancing your skills and expertise.

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What is the salary range for a Senior Engineer - AI/ML Security at American Express?

The salary range for a Senior Engineer - AI/ML Security at American Express starts from $110,000 and can go up to $190,000 annually, plus bonuses and benefits. Several factors, including your experience and location, will play a role in determining your final compensation. Along with a competitive salary, the benefits package includes health insurance, retirement savings plans with company matches, and extensive support for your well-being.

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Common Interview Questions for Senior Engineer - AI/ML Security
Can you explain the secure model development life cycle and its importance?

Certainly! The secure model development life cycle involves implementing processes and practices that ensure models are built with security in mind from the outset. This includes validating data inputs, assessing model vulnerabilities, and designing safeguards against adversarial attacks. During your interview, emphasize the need for integrating security at each stage of the model's development and deployment to protect against potential threats.

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What techniques would you use to evaluate the robustness of AI/ML models?

When evaluating the robustness of AI/ML models, I would apply stress testing methodologies and adversarial testing techniques. These might involve generating adversarial inputs to determine how the model responds under stress and ensuring that performance remains consistent. Highlight your familiarity with various testing frameworks and your ability to interpret results to improve model security in your response.

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How do you approach integrating AI security into existing MLOps processes?

To integrate AI security into MLOps processes, I would work collaboratively with cross-functional teams to ensure that security checks are built into the CI/CD pipeline. This may include automated vulnerability scans, monitoring tools to detect anomalies, and establishing security checkpoints throughout the deployment stages. Stress the importance of working with agile methodologies to iterate on security practices as technology evolves.

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What experience do you have with AI risk management frameworks?

In my previous roles, I've gained hands-on experience with several AI risk management frameworks, including those focusing on ethical AI and compliance with regulations. I would discuss specific frameworks you've implemented and how they've guided your decisions in developing secure AI applications. It's also beneficial to mention any adjustments you've had to make in response to emerging risks in the AI landscape.

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Can you describe a time when you had to troubleshoot an AI/ML security incident?

Absolutely! Share a specific example of an incident where you identified a security vulnerability in an AI/ML model. Be sure to explain how you diagnosed the issue, the steps you took to mitigate the risk, and the lessons learned from that experience. This not only demonstrates your problem-solving skills but also your ability to adapt and improve security practices.

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What programming languages and tools do you prefer for data science projects, and why?

I prefer languages like Python and R for data science projects due to their rich ecosystems of libraries and tools tailored for machine learning, such as TensorFlow and Scikit-learn. During your interview, detail how you utilize these tools to streamline processes and improve modeling accuracy, emphasizing your hands-on experience with them in practical applications.

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How do you stay updated on the latest trends in AI/ML security?

I stay informed on the latest trends in AI/ML security by regularly attending industry conferences, participating in online communities, and following reputable publications. Sharing articles or findings from relevant research could demonstrate your active engagement with the field. This is a good opportunity to mention your own contributions, such as publications or open-source projects.

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What are the challenges you've faced in deploying AI/ML models to cloud environments?

Deploying AI/ML models to cloud environments presents various challenges, including managing cost efficiency, ensuring scalability, and maintaining security compliance. Discuss a particular instance where you navigated one of these challenges, the solution you implemented, and the results achieved. This showcases your problem-solving abilities in real-world scenarios.

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Can you explain what adversarial robustness means in the context of AI?

Adversarial robustness refers to the ability of an AI model to withstand attempts to mislead it with maliciously crafted inputs. In an interview, focus on how you have tested or improved the robustness of models by employing various techniques, such as adversarial training or model ensembling, to ensure their resistance to potential attacks.

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What steps would you take to establish AI/ML security standards within a team?

To establish AI/ML security standards within a team, I would first assess existing practices and identify areas that need improvement. Then, I would collaborate with stakeholders to create clear guidelines aimed at embedding security throughout the development process. Discuss how you would conduct training workshops and create documentation to ensure that all team members adhere to these standards effectively.

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American Express is a multinational financial services corporation and global leader in providing personal, small business, and corporate credit cards.

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Badge Family FriendlyBadge Office VibesBadge Work&Life BalanceBadge Rapid Growth
CULTURE VALUES
Inclusive & Diverse
Empathetic
Collaboration over Competition
Growth & Learning
Transparent & Candid
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Mental Health Resources
Life insurance
Disability Insurance
Child Care stipend
Employee Resource Groups
Learning & Development
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Full-time, hybrid
DATE POSTED
April 3, 2025

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