Senior AI Engineer I

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 committed to delivering innovative customer experiences through cutting-edge technology and AI.

At American Express, you will work on next-generation Agentic AI platforms, large-scale data and AI systems, and cloud-native engineering solutions that power intelligent business processes across the enterprise. You will collaborate with world-class engineers, data scientists, architects, and product teams to design, build, deploy, and scale mission-critical AI solutions.

Join Team Amex and help us shape the future of Enterprise AI. We are seeking a highly skilled Senior AI Engineer to lead the design, development, deployment, and scaling of enterprise-grade Agentic AI solutions on Google Cloud Platform (GCP).

This role combines expertise across GenAI, LangGraph workflow orchestration, distributed data engineering, cloud-native architectures, and MLOps. The ideal candidate will build production-ready AI systems capable of processing large-scale enterprise data while ensuring reliability, governance, observability, and performance.

The engineer will play a critical role in establishing scalable AI pipelines, multi-agent architectures, retrieval systems, and intelligent workflow orchestration capabilities that drive business outcomes across the organization.

- Bachelor's or master’s degree in computer science,Engineering, or related field.
- 8+ years of software engineering experience with AI/ML or GenAI engineering.
- Strong experience building production systems in Python.
- Hands-on experience with LangGraph, LangChain, CrewAI, AutoGen, or equivalent agent orchestration frameworks.
- Experience deploying applications on Google Cloud Platform (GCP).
- Strong background in data engineering, distributed systems, and large-scale data processing.
- Experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and GKE.
- Experience building RAG, Vector Search, and Knowledge Graph solutions.
- Experience with Kubernetes, Docker, CI/CD, and infrastructure automation.
- Strong understanding of software design patterns, distributed architectures, and microservices.
- Experience with PostgreSQL, Redis, and NoSQL technologies.
- Knowledge of observability, monitoring, and production support processes.