At 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. As part of Team Amex, you'll experience this 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.
How will you make an impact in this role?
The Data Analytics Solutions – Emerging Technologies team is seeking a highly skilled and visionary Senior Engineer – Artificial Intelligence to design and deliver advanced AI solutions that address complex challenges in Technology Risk and Information Security.
This role is pivotal in driving our mission to build intelligent, secure, and adaptive systems leveraging Generative AI, Agentic AI, and Classical Machine Learning. You'll be part of a forward-looking team that thrives on rapid experimentation, bold ideas, and transforming innovation into real-world, production-ready applications that shape the future of cybersecurity.
If you're an AI innovator who thrives at the cutting edge, this is your opportunity to turn breakthrough ideas into lasting impact.
Key Responsibilities:
Design and deploy AI applications powered by Large Language Models (LLMs), RAG, and agentic frameworks such as LangChain, LangGraph, or AutoGen.
Implement classical ML models (e.g., classification, clustering, anomaly detection, NLP) and advanced statistical models to support predictive and prescriptive analytics.
Build scalable, cloud-native pipelines for model training, evaluation, deployment, and monitoring.
Translate complex cybersecurity and technology risk use cases into practical, scalable AI products — including dashboards, APIs, and autonomous agents.
Evaluate AI models and systems across modalities using rigorous metrics — including accuracy, latency, robustness, explainability, and fairness — to ensure real-world performance.
Ensure adherence to enterprise standards for model governance, security, and responsible AI.
Collaborate closely with data scientists, engineers, and cybersecurity stakeholders to deliver AI-driven capabilities that drive measurable business value.
Lead a culture of continuous innovation, promoting rapid prototyping and iterative experimentation.
Contribute to ongoing optimization of platforms, tools, and practices for safer, faster, and more efficient AI product delivery.
Requirements & Skills:
Bachelor’s degree in computer science, Data Science, Statistics, Engineering, Mathematics, or a related field; Master’s degree preferred.
Minimum 5 years of experience designing, developing, and deploying AI/ML solutions in production environments.
Deep hands-on expertise in Generative AI, LLMs, and building autonomous agent-based systems.
Strong foundation in classical ML algorithms such as regression, clustering, decision trees, NLP, and probabilistic models.
Demonstrated experience in evaluating AI systems across GenAI, Agentic AI, and classical ML using clear, measurable metrics.
Knowledge of model lifecycle management, model governance protocols, and MLOps best practices.
A solution-oriented mindset with the ability to execute quickly and responsibly in complex environments.
Domain experience in Cybersecurity or Technology Risk is a strong advantage but not required.
Technical Experience:
Hands-on experience with most of the following tools, frameworks, and technologies is expected:
Development & Libraries
Python, Jupyter Notebooks, VS Code, PyCharm, Github Copilot
PyTorch, TensorFlow, scikit-learn
Vector databases: pgVector, Milvus
Generative & Agentic AI
Hugging Face Transformers
LangChain, LangGraph, AutoGen
Orchestration & Model Serving
Argo Workflows, Kubeflow Pipelines, MLRun
vLLM, Triton Inference Server
Containers & CI/CD
Docker, Kubernetes
Jenkins, XL Release
Data & Observability
SQL, NoSQL, Spark, Dask, Apache Kafka, Apache NiFi
Elasticsearch, Kibana, Prometheus
APIs & Deployment
RESTful API and web application development
Experience with cloud platforms: AWS, Azure, or Google Cloud