Python Backend Software Engineer III - AWS / Databricks

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. 

As a Software Engineer III at JPMorganChase within the Commercial & Investment Bank Payments Technology team in Tampa, FL, you will design, build, and maintain the backend platform services that enable clients to manage payments globally — spanning liquidity solutions, commerce, clearing, and working capital. You will work alongside talented engineers and cross-functional partners to deliver resilient, scalable systems that process transactions at enterprise scale. This is an opportunity to deepen your technical craft, contribute to meaningful platform modernization, and grow your career within one of the world's leading financial institutions.

Job responsibilities

• Execute software solutions across design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions and break down complex technical problems
• Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems across the payments platform
• Leverage enterprise-authorized AI coding assist tools to improve code quality, delivery speed, and productivity — including code generation, refactoring, unit test creation, and documentation — while validating outputs through peer review, automated testing, and secure coding standards; contribute learnings and reusable patterns to improve broader team effectiveness
• Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
• Produce architecture and design artifacts for complex applications while ensuring design constraints are met throughout software code development
• Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
• Proactively identify hidden problems and patterns in data, using insights to drive improvements to coding hygiene and system architecture
• Contribute to software engineering communities of practice and events that explore new and emerging technologies
• Add to a team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 3+ years applied experience
• Proficiency in Python or another object-oriented language (Java, C++) with a proven track record of high-quality, successful delivery
• Hands-on experience building and operating distributed systems with Apache Kafka, including partitions and consumer groups, exactly-once semantics, and schema management
• Strong experience with cloud infrastructure on AWS and infrastructure-as-code tooling (e.g., ECS/EKS, Lambda, API Gateway, RDS, S3, KMS, IAM, CloudWatch; Terraform or CloudFormation)
• Strong grasp of event-driven and microservices architecture, REST APIs, and asynchronous messaging patterns
• Proven experience implementing CI/CD pipelines, automated testing, and safe deployment strategies such as blue/green or canary releases
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
• Solid reliability and observability fundamentals, including retries, idempotency, timeouts, and logs/metrics/tracing
• Experience leading projects or teams, setting technical direction, and delivering complex production systems
• Experience working in Agile or Scrum delivery environments
• Hands-on experience with observability tooling such as Datadog or Grafana

Preferred qualifications, capabilities, and skills

• Banking or payments domain knowledge, including authorization, clearing and settlement, transaction processing, reconciliation, ISO 20022 standards, and payment channels such as SWIFT, pain, or MX messaging formats
• Experience applying observability practices — metrics, logs, and tracing — and site reliability engineering principles for production systems
• Hands-on use of production observability tooling such as Splunk, Dynatrace, or Grafana
• Cloud knowledge on AWS or Azure, including compute, storage, networking, and identity and access management; familiarity with containerization (Docker) and orchestration (Kubernetes) is a plus
• Experience applying machine learning concepts or integrating machine learning models into backend platform services

About Company

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