Sr. Software Engineer I - Global Servicing Technology

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.

The Technology organization enables and accelerates the company’s growth strategies, delivering global capabilities and services in support of Amex’s customers and colleagues, while maintaining 24/7 servicing and availability to ensure an uninterrupted, high-quality customer experience. Technology provides the foundation for everything we do in the company while driving differentiation through building and leveraging innovative technology and data insights.

The Servicing Experiences Technology (SET) organization enhances Servicing Experiences by building smarter platforms with seamless automation and AI-driven insights- empowering Colleagues and Customers alike.

• Provide thought leadership, engineering expertise, and direction to the engineering teams; be versatile and be able to collaborate with business stakeholders, product teams and cross functional technology groups to drive continuous delivery.
• Drive user story analysis and elaboration, design and develop software applications, and test and build automation tools.
• Own all technical aspects of software development (architecture, design, and development of systems) for assigned applications.
• Perform hands-on software development, writing code, API specs, doing proof of concepts, conducting code reviews, and testing in ongoing sprints.
• Drive consistent development practices - tools and common components.
• Develop deep understanding of tie-ins with other systems and platforms within the supported domains.
• Work with technical product managers contributing to blueprints and assisting with annual planning of feature sets.
• Identify opportunities for adopting new technology to solve existing needs and predicting future challenges.
• Effectively communicate to internal and external business partners on solution design.

• 8+ years of professional experience designing and building cloud-native data platforms, scalable data pipelines, and distributed data processing solutions.
• Strong experience designing and implementing batch and streaming data ingestion frameworks, ETL/ELT pipelines, and reusable data processing patterns using Python, PySpark, Spark, Dataproc, SQL, or equivalent distributed data processing technologies.
• Experience designing and developing data platforms on Google Cloud Platform (preferred) or AWS/Azure using services such as BigQuery, Cloud Storage, Pub/Sub, Dataproc, Cloud Composer, Cloud Run, Cloud Functions, and related cloud-native data services.
• Strong understanding of Contact Center as a Service (CCaaS) platforms and customer interaction data generated across voice, chat, IVR, dialers, Agent Assist, Speech-to-Text (STT), Text-to-Speech (TTS), conversation transcripts, interaction events, and operational metrics.
• Experience defining canonical data models, metadata management, data quality frameworks, and reusable data products to support enterprise analytics, reporting, and downstream applications.
• Experience integrating CCaaS platforms and enterprise systems using REST APIs, event streaming, messaging technologies, webhooks, and batch or real-time ingestion patterns.
• Strong experience with Apache Kafka, Google Pub/Sub, or similar event streaming technologies, including designing scalable and resilient data ingestion patterns.
• Strong proficiency in SQL, data modeling, data virtualization, semantic datasets, and working with relational and NoSQL databases supporting analytical and operational workloads.
• Experience enabling enterprise analytics through BigQuery, Metrics as a Service, reusable data services, and cloud-native analytical platforms.
• Experience implementing CI/CD practices, deployment automation, and engineering best practices using Git, Jenkins, Docker, Kubernetes, Terraform, or similar DevOps technologies.
• Experience leading technical design discussions, mentoring engineers, conducting design and code reviews, and driving engineering best practices across multiple teams.
• Excellent communication and stakeholder management skills with the ability to collaborate across Product, Engineering, Architecture, Analytics, and Business organizations to deliver scalable data platform solutions.

Good to Have: 

• Experience with Java and Spring Boot for backend services supporting enterprise data platforms or APIs.
• Experience with Context Management, Customer Journey Analytics, Customer Interaction Platforms, Contact Center Analytics, or Customer 360 solutions.
• Familiarity with Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), semantic search, vector
  databases, AI agents, or AI-powered analytics.
• Experience with data virtualization, enterprise semantic layers, or reusable data services supporting analytics and reporting.
• Experience modernizing enterprise data platforms or migrating analytical workloads to Google BigQuery and cloud-native data ecosystems.
• Exposure to enterprise data governance, metadata management, data lineage, cataloging, or observability platforms.
• Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.