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Senior Engineer - AI/ML Security - job 1 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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What You Should Know About Senior Engineer - AI/ML Security, American Express

Join American Express as a Senior Engineer - AI/ML Security and be part of a dynamic team that is eager to push the boundaries of technology while ensuring the safety and integrity of AI applications. In this role, you'll take lead in establishing security measures across various projects, focusing on robust AI practices and risk management processes. You'll work closely with cross-functional teams to design and implement secure development practices, and you'll have the freedom to innovate using the latest technologies. American Express prides itself on fostering a diverse and inclusive work environment where every opinion counts, and collaboration thrives. Your responsibilities will include delivering AI/ML security initiatives, assessing open-source security options, and integrating measurement tools into the AI ecosystem. Not only will you play a key role in enhancing AI/ML security, but you'll also receive dedicated time for your professional development, ensuring your skills remain cutting-edge. At American Express, you are not just an employee; you are part of a team committed to back each other and our customers. If you're passionate about creating safe and reliable AI applications and want to make a significant impact, this is the perfect opportunity for you to grow and succeed in a supportive workspace. Let’s lead the way together!

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

A Senior Engineer - AI/ML Security at American Express is responsible for implementing security measures in AI/ML models, leading various AI safety initiatives, and ensuring compliance with risk management processes. This role focuses on developing robust AI practices, conducting assessments to measure AI model vulnerabilities, and integrating tools for testing and managing risks in AI applications.

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What qualifications are required for the Senior Engineer - AI/ML Security position at American Express?

Candidates for the Senior Engineer - AI/ML Security role at American Express should hold a Bachelor's Degree in fields like Data Science, Statistics, Computer Science, or Software Engineering, along with a minimum of 3 years of relevant experience in machine learning development and software engineering. A Master’s degree and certifications in Machine Learning Operations are preferred qualifications.

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What are the preferred skills for a Senior Engineer - AI/ML Security at American Express?

Preferred skills for the Senior Engineer - AI/ML Security role at American Express include strong knowledge of adversarial robustness techniques, AI risk management frameworks, and extensive hands-on experience with deploying AI/ML models. Familiarity with MLOps, cloud architecture, and various programming languages and tools used in data science is also highly valued.

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

American Express is committed to the professional development of its employees, including the Senior Engineer - AI/ML Security role, by providing dedicated time for learning new skills and technologies. Colleagues have access to career development training, mentorship opportunities, and resources to invest in their ongoing education and professional growth.

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

The expected salary range for a Senior Engineer - AI/ML Security at American Express is between $110,000.00 to $190,000.00 annually, which is complemented by bonuses and a comprehensive benefits package. Factors such as location and relevant experience will be considered when determining final compensation.

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Common Interview Questions for Senior Engineer - AI/ML Security
Can you explain what adversarial robustness means in the context of AI/ML?

Adversarial robustness refers to the ability of an AI/ML model to maintain performance when faced with malicious inputs designed to deceive it. In an interview, describe how you've previously implemented techniques to enhance model robustness and share specific examples or results from your experiences.

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How do you approach implementing a secure model development lifecycle for AI/ML at American Express?

Explain your methodology for embedding security throughout the model development lifecycle. Discuss the importance of regular assessments, the use of automated tools, and how to incorporate feedback from each stage of development to continuously enhance security protocols.

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What experience do you have with MLOps practices?

Share specific experiences where you applied MLOps principles in your previous roles. Illustrate the tools you used, how you managed model deployments, and any collaborative efforts with development and operations teams that improved operational efficiency.

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How would you evaluate open-source AI security libraries for use in enterprise systems?

Discuss your evaluation process for assessing open-source AI security libraries, focusing on criteria such as community support, documentation, security audits, and how you would ensure the libraries align with the security standards of American Express.

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What key considerations do you think should be made when incorporating LLM applications into an organization?

Highlight considerations such as understanding data privacy concerns, ensuring robust security protocols, implementing appropriate usage policies, and continuously monitoring the effectiveness of these models in meeting organizational objectives.

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Can you detail a project where you conducted stress testing on AI/ML systems?

Provide a structured overview of a past project involving stress testing, including the objectives, the methodologies used (like simulation or performance metrics), and the outcomes or findings that informed best practices moving forward.

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What are the challenges you have faced in deploying AI/ML models in cloud environments?

Discuss specific challenges such as optimization for cloud performance, cost management, and security concerns that you've navigated. Illustrate how your solutions facilitated successful cloud-based deployments while addressing these challenges effectively.

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In your opinion, what are the most critical AI risk management frameworks?

Share your insights on established AI risk management frameworks, discussing their components such as governance, accountability, and compliance. Illustrate how you've applied these frameworks in practice and their impact on AI project success.

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

Outline your approach to staying current on AI/ML security trends, including resources like industry publications, forums, conferences, and online learning platforms. Discuss how you incorporate new knowledge into your work practices to ensure ongoing improvement.

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What do you think are some best practices for ensuring the responsible use of AI applications?

Discuss best practices such as developing transparent workflows, setting ethical guidelines for use, monitoring model performance, and regularly updating compliance protocols. Share examples of how you’ve implemented these practices in previous roles.

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

2285 jobs
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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 4, 2025

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