AI Engineer II

About The Role

At American Express, technology is central to innovation, growth, and delivering exceptional customer experiences. Joining Amex Tech means contributing to a global engineering organization shaping the future of commerce through cutting-edge platforms, data, and Artificial Intelligence. Teams build scalable, secure, and intelligent systems powering seamless experiences for customers and colleagues worldwide. Artificial Intelligence is a key driver of this transformation, embedded into core sales and customer platforms for intelligent automation, advanced decisioning, and personalized engagement, while ensuring strong governance, reliability, and responsible use at enterprise scale. You will contribute to the development of enterprise AI platforms, reusable frameworks, and engineering best practices.

Key Responsibilities

• Develop AI-powered solutions integrating GenAI capabilities (prompts, AI agents, copilots, 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.

Requirements & Tech Stack

• Python (strong programming skills, solid command of data structures, algorithms, clean, correct, efficient code)
• SQL (strong skills for querying and manipulating enterprise datasets)
• Machine Learning & GenAI Fundamentals (working knowledge of model architectures like Transformers, LLMs, embeddings, prompt engineering, RAG, core evaluation metrics like precision/recall)
• AI/ML System Design (ability to design AI solution components and feature-level pipelines, e.g., a RAG pipeline for document QA)
• GenAI Platforms: Hands-on experience with Azure OpenAI, OpenAI/ChatGPT, Microsoft Copilot, Gemini, or Claude.
• APIs and integrating third-party services.
• Vector databases and embeddings (e.g., FAISS, Pinecone, pgvector).
• Agentic frameworks and orchestration tools (e.g., LangChain, LangGraph, Semantic Kernel, AutoGen).
• Familiarity with cloud platforms (Azure, AWS, or GCP) and containerization (Docker, Kubernetes).
• MLOps/LLMOps practices (CI/CD, monitoring, evaluation frameworks).
• Dashboarding/BI tools (e.g., Power BI or Tableau).
• Awareness of model optimization concepts (e.g., quantization like 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).

Qualifications

• 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.
• Analytical and problem-solving skills with strong attention to detail and ability to convert business requirements into logical workflows.
• Behavioral / Collaboration: Comfort handling ambiguity, collaborating cross-functionally, and communicating clearly in a team setting.