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 Inference Engineer is responsible for independently designing, optimizing, and operating scalable production inference services that enable enterprise AI and machine learning solutions. This role partners with stakeholders to translate business and technical requirements into reliable model-serving capabilities, build efficient integration patterns and data pipelines, and ensure solutions meet established enterprise architecture standards for performance, reliability, observability, compliance, and production readiness.
Responsibilities- Mentors junior AI Engineers and cross-functional team of colleagues, fostering a culture of excellence and innovation
- Integrates AI models into production systems in collaboration with cross-functional teams, ensuring effective integration into existing production systems
- Maintains strict adherence to model governance, security, and compliance standards
- Collaborates with engineers to deliver scalable AI solutions by integrating models that meet both technical and business requirements
- Translates business requirements into AI-driven technical solutions, ensuring that business needs are converted into actionable models and algorithms
- Creates end-to-end machine learning operations pipelines for scalable model deployment, facilitating seamless deployment, monitoring, and maintenance of AI models
- Collaborates and co-creates effectively with teams in product and the business to align technology initiatives with business objectives
- Designs and operates scalable production AI systems, integrating ML models, LLMs, and intelligent services across multiple components
- Ensures AI systems adhere to enterprise standards for reliability, safety, explainability, observability, and compliance, mentoring others on best practices
- Designs and operates scalable inference services, including performance, reliability, observability, and production readiness.
- Evaluates serving approaches and optimizes latency, throughput, accelerator utilization, and cost for assigned workloads.
- Partners across platform, infrastructure, security, evaluation, and application teams and mentors less-experienced engineers.
Education and Knowledge
- Bachelor's degree in Computer Science, Machine Learning, Data Science, and/or comparable experience; advanced degree preferred
- Advanced knowledge of machine learning techniques and performance optimization
- Strong understanding of AI system architectures including LLM ecosystems, retrieval systems, orchestration frameworks, and evaluation methodologies
- Strong knowledge of production model serving, inference optimization, GPU fundamentals, Kubernetes, APIs, and distributed systems.
Ability to evaluate technical alternatives and make sound service-level design decisions within established architecture.
Work Experience
- 5+ years software development experience, including hands-on experience in machine learning, AI technologies, and Agentic AI solutions.
- Experience in working with large language models (LLMs), especially GPT-3.5/4 or similar AI models
- Experience in languages such as Python, R, Java, or C++
- Experience in deploying AI models and pipelines using machine learning operations tools
- Experience in machine learning algorithms and experience applying them to real-world problems
- Experience in continuous integration/continuous deployment pipelines and containerized deployments
- Experience delivering end-to-end AI systems in production, including design and operational ownership
- Experience with distributed systems design, scalable APIs, and cloud-native AI infrastructure, including monitoring and optimization
- Advanced expertise in a technical domain and moderate expertise in a new, different technical domain
- Demonstrated experience independently building and operating production inference services.
- Experience with model-serving frameworks, containerized GPU workloads, and performance or reliability optimization.
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
- Bachelor's degree in Computer Science, Machine Learning, Data Science, or comparable experience
- Advanced knowledge of machine learning techniques and performance optimization
- Strong understanding of AI architectures, LLM ecosystems, retrieval systems, orchestration frameworks, and evaluation methodologies
- Strong knowledge of production model serving, inference optimization, GPU fundamentals, Kubernetes, APIs, and distributed systems
- Ability to evaluate technical alternatives and make service-level design decisions
- 5+ years of software development experience, including hands-on machine learning, AI, and Agentic AI experience
- Experience with large language models, especially GPT-3.5, GPT-4, or similar models
- Experience with Python, R, Java, or C++
- Experience deploying AI models and pipelines using MLOps tools
- Experience applying machine learning algorithms to real-world problems
- Experience with CI/CD pipelines and containerized deployments
- Experience delivering end-to-end AI systems in production with design and operational ownership
- Experience with distributed systems design, scalable APIs, and cloud-native AI infrastructure
- Experience with monitoring and optimization of AI systems
- Advanced expertise in a technical domain and moderate expertise in another technical domain
- Demonstrated experience independently building and operating production inference services
- Experience with model-serving frameworks, containerized GPU workloads, and performance or reliability optimization
- 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.
