American Express
Senior Staff AI Engineer - Global Infrastructure
New York, NY +2 · Hybrid · Senior Staff · Full-time · Posted Oct 2, 2026
- Location
- New York, NY
Sunrise, FL
Phoenix, AZ - Experience
- 12+ years in AI/ML engineering, AI infrastructure, platform engineering, data engineering, or related fields.
- Education
- MS/PhD in Artificial Intelligence, Machine Learning, Computer Science, or related discipline preferred.
- Visa sponsorship
- American Express may provide visa sponsorship for certain positions, depending on factors such as business unit requirements, the nature of the position, cost, and applicable laws.
About the job
Leads enterprise-scale AI architecture and implementation across infrastructure and agentic AI systems, setting technical direction and advancing secure, reliable, scalable, and responsible AI platforms.
What you'll do
- Defines architecture and engineering patterns for agentic AI, retrieval, model integration, inference, observability, evaluation, and safety.
- Guides cross-team AI initiatives, technical reviews, and enterprise AI engineering strategy.
- Partners with business and technical leaders, evaluates emerging AI technologies, and mentors senior engineers.
What they ask for
- Deep knowledge of machine learning and deep learning systems, Generative AI and LLMs, AI infrastructure, agentic AI, and distributed systems.
- Experience architecting end-to-end AI/ML platforms and designing and operating GPU-based AI infrastructure.
- Hands-on experience with Python and modern AI/ML frameworks; experience with cloud-native and Kubernetes-based platforms.
- Experience leading cross-functional initiatives, mentoring engineers, and working in regulated environments such as financial services.
Nice to have
- MS/PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related discipline.
- Knowledge of DevOps and CI/CD platforms such as Harness.
Pay
$144250 - $256250 annually (base salary)
Tools
GPU, Kubernetes, APIs, Harness, Python, PyTorch, TensorFlow, Scikit-learn
AI focus
Enterprise AI architecture and infrastructure, including agentic AI, Generative AI and LLMs, retrieval-augmented generation, model serving and inference, evaluation, observability, safety, and governance.
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