Job Description

Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success. Because Amex Tech is powered by our technology, our culture, and our colleagues.

We are looking for a motivated and hands-on Full Stack Software Engineer with strong Python programming fundamentals, experience working with Relational and NoSQL databases, and practical exposure to Generative AI (GenAI) and Agentic AI development. The ideal candidate will be passionate about building scalable applications, integrating Large Language Models (LLMs), implementing Retrieval-Augmented Generation (RAG) solutions, and developing AI-powered workflows using frontier and open-source models.

This role offers an opportunity to work on both modern AI technologies and contributing to enterprise-grade software applications.

Key Responsibilities

1. Python & Backend Development

• Design, develop, test, and maintain Python-based applications and backend services.
• Build and integrate RESTful APIs using frameworks such as FastAPI or Flask.
• Write clean, modular, reusable, and maintainable code.
• Implement unit tests, debugging, logging, and error handling.
• Collaborate with cross-functional teams to deliver reliable software solutions.

1. Database Development

• Work with relational databases such as PostgreSQL, Oracle
• Develop SQL queries, manage schemas, and perform basic query optimization.
• Work with NoSQL databases such as Couchbase, Cassandra, MongoDB, DynamoDB
• Implement data ingestion, retrieval, and integration workflows.

1. Generative AI & Vector Databases

• Develop GenAI-powered applications using Large Language Models.
• Build and integrate Retrieval-Augmented Generation (RAG) pipelines.
• Work with vector databases.
• Implement document ingestion, chunking, embeddings, semantic search, and retrieval workflows.
• Integrate LLM APIs and develop effective prompt engineering strategies.

1. Agentic AI Development

• Develop AI agents capable of executing tasks, invoking tools, and interacting with external systems.
• Build agentic workflows using frameworks such as LangChain, LangGraph, or similar technologies.
• Integrate frontier LLMs & open-source/open-weight LLMs.
• Implement basic agent orchestration, tool calling, state management, and workflow automation.
• Evaluate agent performance, reliability, and response quality.

1. Software Engineering & Collaboration

• Use Git for version control and collaborate through code reviews.
• Participate in Agile development processes.
• Write technical documentation and support application troubleshooting.
• Follow secure coding practices and data privacy requirements.
• Contribute to continuous improvement of AI-enabled applications.

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related discipline, or equivalent practical experience.
• 1-3 years of enterprise experience in software development using Python.
• Strong understanding of Python programming, object-oriented programming, data structures, and APIs.
• Hands-on experience with at least one Relational database and one NoSQL database.
• Working knowledge of SQL, database design, and data retrieval.
• Practical experience integrating LLMs into Python applications.
• Understanding of embeddings, vector databases, semantic search, and RAG architectures.
• Familiarity with frontier and open-source LLMs.
• Basic understanding of agentic AI concepts, tool calling, and AI workflow orchestration.
• Experience using Git and common development tools.
• Knowledge of Docker, CI/CD pipelines, and deployment practices.
• Strong problem-solving, debugging, and communication skills.

Preferred Qualifications

• Experience with LangChain, LangGraph or similar frameworks.
• Familiarity with model-serving tools such as Ollama, vLLM.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with LLM evaluation, observability, prompt optimization, and guardrails.
• Understanding of MCP (Model Context Protocol) and AI tool integration.
• Exposure to enterprise security, authentication, and access control.

Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.