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.
ResponsibilitiesKey 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.
2. 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.
3. 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.
4. 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.
5. 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.
Skills Required
- Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related discipline, or equivalent practical experience
- 1-3 years of enterprise software development experience using Python
- Strong understanding of Python, 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
- Experience with LangChain, LangGraph, or similar frameworks
- Familiarity with model-serving tools such as Ollama or vLLM
- Experience with AWS, Azure, or Google Cloud
- Familiarity with LLM evaluation, observability, prompt optimization, and guardrails
- Understanding of MCP and AI tool integration
- Exposure to enterprise security, authentication, and access control
- Eligibility to work in the United States without visa sponsorship
American Express Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about American Express and has not been reviewed or approved by American Express.
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Strong & Reliable Incentives — Bonuses are often viewed as strong and materially boost total compensation when combined with benefits. Company-performance bonuses are highlighted as a recurring strength.
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Leave & Time Off Breadth — Paid time off and paid leave are frequently highlighted as strengths within the total rewards package. These policies support work-life balance and contribute meaningfully to overall satisfaction.
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Retirement Support — Retirement benefits are frequently mentioned as a positive component of the package. These offerings add tangible value beyond base salary.
American Express Insights
What We Do
At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly striving to uphold our powerful backing promise to our customers and each other every day. These beliefs have been our North Star for 170 years as our business transformed – from helping evacuate travelers during World Wars, to ensuring the safety of our customers’ funds during the Great Depression in the U.S., to creating the Shop Small® movement to help small businesses recover from the Financial Crisis, to providing aid to communities impacted by many natural disasters and so much more. For generations, the key to our success has been the determination and resilience of our American Express colleagues. Now, as a globally integrated payments company, we work together to provide customers with access to products, insights and world-class experiences that enrich lives and build business success. Join us and let’s lead the way together.
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