AI Engineer II

At American Express, technology is at the core of how we innovate, grow, and deliver exceptional customer experiences. Joining Amex Tech means being part of a global engineering organization that is shaping the future of commerce through cutting-edge platforms, data, and Artificial Intelligence. Our teams build scalable, secure, and intelligent systems that power seamless experiences for customers and colleagues worldwide.

Artificial Intelligence is a key driver of this transformation. From intelligent automation to advanced decisioning and personalized engagement, we are embedding AI into core sales and customer platforms—while ensuring strong governance, reliability, and responsible use at enterprise scale

You will also contribute to the development of enterprise AI platforms, reusable frameworks, and engineering best practices while ensuring AI solutions are reliable, secure, and aligned with responsible AI and governance standards.

Develop AI-powered solutions integrating GenAI capabilities - prompts, AI agents, copilots, and RAG pipelines to improve operational productivity and automate manual processes.

Identify and implement opportunities to automate workflows using Python, SQL, GenAI, and workflow automation tools.

Write clean, maintainable, production-quality code and participate in code reviews and testing.

Test and evaluate AI outputs for accuracy, relevance, and reliability using appropriate evaluation techniques.

Stay current with emerging AI technologies and tools, and share recommendations with the team.

Follow responsible AI practices, data privacy, security, and governance across all GenAI solutions.

Collaborate within an agile team and support the deployment and ongoing maintenance of solutions in production.

Bachelor's degree in computer science, Engineering, or a related field, or equivalent practical experience.

2-5 years of software engineering or applied AI/ML experience, including hands-on work building and shipping GenAI or AI-powered solutions.

Coding & Algorithms: Strong programming skills in Python with solid command of data structures, algorithms, and the ability to write clean, correct, efficient code.

Machine Learning Domain: Working knowledge of ML and GenAI fundamentals - model architectures (e.g., Transformers), LLMs, embeddings, prompt engineering, RAG, and core evaluation metrics (precision/recall).

AI/ML System Design: Ability to design AI solution components and feature-level pipelines (e.g., a RAG pipeline for a document QA use case), making sound, practical design choices.

Behavioral / Collaboration: Comfort handling ambiguity, collaborating cross-functionally, and communicating clearly in a team setting.

Strong SQL skills for querying and manipulating enterprise datasets.

Hands-on experience with GenAI platforms such as Azure OpenAI, OpenAI/ChatGPT, Microsoft Copilot, Gemini, or Claude.

Experience working with APIs and integrating third-party services.

Analytical and problem-solving skills with strong attention to detail and the ability to convert business requirements into logical workflows.

Familiarity with cloud platforms (Azure, AWS, or GCP) and containerization (Docker, Kubernetes).

Experience with vector databases and embeddings (e.g., FAISS, Pinecone, pgvector).

Experience with agentic frameworks and orchestration tools (e.g., LangChain, LangGraph, Semantic Kernel, AutoGen).

Exposure to MLOps/LLMOps practices - CI/CD, monitoring, and evaluation frameworks for AI systems.

Experience with dashboarding/BI tools such as Power BI or Tableau.

Awareness of model optimization concepts such as quantization (e.g., INT8/FP8).

Knowledge of another object-oriented language (e.g., Java, C++, or Go).

Experience building AI solutions in a regulated industry (e.g., fintech, healthcare).