The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.
The Implementation / ML Ops Engineer is responsible for implementing, deploying, and supporting AI/ML models within approved GPU-enabled environments. This role packages and operationalizes trained models, supports scalable data and deployment pipelines, integrates models with production systems, and helps maintain reliable monitoring, validation, versioning, and rollback processes. The engineer works within established enterprise patterns, security controls, and AI governance standards while collaborating with product, technology, and business partners to deliver production-ready AI capabilities.
Responsibilities- Implements model monitoring and evaluation techniques to improve AI system performance over time
- Ensures AI solutions adhere to governance, security, and compliance requirements
- Provides support and troubleshooting for AI models and data processing pipelines in production
- Collaborates effectively with teams in product and the business to align technology initiatives with business objectives
- Performs standard tasks within established procedures and guidelines; works within established guidelines with some degree of independence for routine tasks
- Develops and integrates components of production AI systems, including ML models or LLM-based services, with moderate independence
- Applies enterprise standards for observability, safety, and compliance in implemented AI components
- Implements and supports model packaging, validation, versioning, deployment, monitoring, and rollback using approved templates and controls.
- Contributes to CI/CD, container, Kubernetes, registry, testing, and telemetry configurations for assigned workloads.
- Troubleshoots common implementation issues and escalates complex design, optimization, or production problems to senior engineers.
Education and Knowledge
- 2+ years software development, including hands-on experience in machine learning, AI technologies, and Agentic AI solutions.
- Bachelor's degree in Computer Science, Machine Learning, Data Science, and/or comparable experience; advanced degree preferred
- Knowledge of Python and data processing technologies
- Working knowledge of machine learning techniques and model evaluation approaches
- Foundational working knowledge of MLOps or LLMOps, containers, Kubernetes fundamentals, CI/CD, artifact management, testing, and monitoring.
Basic understanding of GPU resource needs, runtime dependencies, scheduling constraints, and enterprise security and change controls.
Work Experience
- Experience in working with large language models (LLMs), especially GPT-3.5/4 or similar AI models
- Experience in languages such as Python or R
- Experience in deploying AI models and pipelines using machine learning operations tools
- Experience in continuous integration/continuous deployment pipelines and containerized deployments
- Experience developing and deploying machine learning or LLM-enabled applications in production or near-production environments
- Practical experience with distributed systems concepts, APIs, and cloud-native infrastructure supporting AI workloads
- Moderate expertise in a specific technical domain
- Some practical experience contributing to software, infrastructure, container, data, or machine learning deployment and automation work.
- Exposure through project, internship, or practical work to containerized deployment, artifact repositories, automated testing, monitoring, versioning, or rollback.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
About UsAt American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
About the TeamWe back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
- 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.
Skills Required
- 2+ years of software development experience, including hands-on machine learning, AI technologies, and Agentic AI solutions
- Bachelor's degree in Computer Science, Machine Learning, Data Science, or comparable experience
- Knowledge of Python and data processing technologies
- Working knowledge of machine learning techniques and model evaluation approaches
- Foundational knowledge of MLOps or LLMOps, containers, Kubernetes, CI/CD, artifact management, testing, and monitoring
- Basic understanding of GPU resource needs, runtime dependencies, scheduling constraints, and enterprise security and change controls
- Experience working with large language models, especially GPT-3.5/4 or similar models
- Experience with Python or R
- Experience deploying AI models and pipelines using machine learning operations tools
- Experience with CI/CD pipelines and containerized deployments
- Experience developing and deploying machine learning or LLM-enabled applications in production or near-production environments
- Practical experience with distributed systems concepts, APIs, and cloud-native infrastructure supporting AI workloads
- Moderate expertise in a specific technical domain
- Practical experience contributing to software, infrastructure, container, data, or machine learning deployment and automation work
- Exposure through projects, internships, or practical work to containerized deployment, artifact repositories, automated testing, monitoring, versioning, or rollback
- Advanced degree
American Express Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about American Express and has not been reviewed or approved by American Express.
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Fair & Transparent Compensation — Pay is considered generally solid for many, with frequent mentions of good compensation alongside strong benefits. Overall sentiment points to many employees feeling adequately paid even if it is not viewed as top-of-market.
American Express Insights
What We Do
At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly striving to uphold our powerful backing promise to our customers and each other every day. These beliefs have been our North Star for 170 years as our business transformed – from helping evacuate travelers during World Wars, to ensuring the safety of our customers’ funds during the Great Depression in the U.S., to creating the Shop Small® movement to help small businesses recover from the Financial Crisis, to providing aid to communities impacted by many natural disasters and so much more. For generations, the key to our success has been the determination and resilience of our American Express colleagues. Now, as a globally integrated payments company, we work together to provide customers with access to products, insights and world-class experiences that enrich lives and build business success. Join us and let’s lead the way together.
