Software Engineer Future Opportunities

American Express invites you to share your resume so you can be considered for future opportunities. The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company. 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. At American Express, AI is reshaping the future of commerce and redefining the experiences our commercial customers and card members expect. Within Amex Technology, we are building platforms, products, and governance that enable agentic AI systems to operate responsibly and at scale across the enterprise. Our focus is on agentic AI development: designing intelligent, adaptive systems that can plan, reason, and act across complex workflows with appropriate levels of autonomy. These systems power autonomous workflows, decision support, and customer-facing experiences—while meeting the high standards for security, explainability, reliability, and compliance required in financial services. We partner closely with product, design, and business teams to deliver agentic capabilities that reduce operational friction, improve decision-making, and transform how customers interact, transact, and grow. As an Software Engineer – Agentic AI , you will be a hands-on builder contributing to the development of production-grade agentic AI systems that securely operate on enterprise and cloud data while serving both internal and customer-facing use cases. You should be experienced and responsible for software design, development, testing, and implementation. Experience must include 1 year of experience with: Any of these - Agile, algorithms, API, API Rest, GIT, J2EE, Java, JavaScript, JDBC, Jenkins, JSON, JUnit, Linux, Log4J, Maven, object-oriented programming, performance tuning, RDBMS, relational databases, REST, Spring, Spring framework, Spring MVC, SQL, Unix, Waterfall, and XML You will work alongside experienced engineers, cloud architects, security engineers, product managers, and designers to design, build, and deploy AI-powered capabilities that automate cloud security, risk management, governance, and operational workflows. This role provides opportunities to grow technical expertise in LLMs, agentic systems, cloud security, and production AI engineering while operating within a highly regulated enterprise environment. This is not a research-only role. You will write production-quality code, contribute to architecture and security design discussions, implement AI-powered cloud security solutions, and support the systems you build throughout their operational lifecycle. What You'll Do Design and implement LLM-powered and agentic AI solutions that automate cloud security, governance, and operational workflows. Build and extend agentic AI workflows capable of reasoning over enterprise security context, invoking cloud security tools, and performing automated actions with appropriate guardrails and human oversight. Develop AI agents that integrate with enterprise cloud platforms, SaaS applications, identity services, CNAPP, CSPM, SSPM, SIEM, and security orchestration platforms. Design and maintain Retrieval-Augmented Generation (RAG) pipelines using enterprise security documentation, cloud architecture, policies, incident data, and operational knowledge while ensuring correctness, privacy, and regulatory compliance. Develop Security-as-Code and Policy-as-Code capabilities that enable AI agents to validate cloud configurations, enforce security guardrails, and recommend or automate remediation activities. Contribute to shared AI infrastructure including LLM services, orchestration frameworks, vector databases, agent evaluation frameworks, and AI observability tooling. Build AI-powered automation for cloud security assessments, threat modeling, security posture analysis, compliance validation, and risk reporting. Participate in operating AI systems in production, including monitoring model performance, evaluating agent behavior, debugging issues, improving reliability, and ensuring secure AI operations. Collaborate with cloud engineering, cybersecurity, platform engineering, product, and business teams to translate security and operational requirements into scalable AI-enabled solutions. Ensure AI systems are designed with enterprise security, governance, explainability, auditability, and responsible AI principles. Minimum Qualifications 2+ years of professional software engineering experience. Some hands-on experience building or contributing to AI-powered features, LLM-based applications, or applied ML systems (professional or project-based). Solid engineering fundamentals in at least one backend language (Java, Python, Go, or TypeScript). Familiarity with APIs, basic cloud concepts, and modern development practices. Interest in agentic AI systems, autonomy, and AI-assisted development workflows. Willingness to learn, take feedback, and grow technical ownership over time. Comfort working in collaborative, cross-functional teams. A strong customer mindset and curiosity about real-world problem solving. Preferred Qualifications Exposure to LLM tooling, prompt engineering, RAG, or agent frameworks through work, coursework, or personal projects. Internship or early-career experience in fintech or other regulated environments. Contributions to open-source projects, hackathons, or side projects related to AI or developer tooling.