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 and Investment Bank, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on Software Engineering and application development and 5+ years applied experience
- Hands‑on Python application development experience
- Proven experience developing, debugging, and maintaining production applications
- Solid understanding of software development best practices including version control, testing, and CI/CD
- Strong problem-solving, communication, and collaboration skills, with the ability to convey design choices and communicate effectively with stakeholders
- Familiarity with Machine Learning Operations (MLOps)
- Experience using AI engineering tools (e.g., GitHub Copilot) for JIRA, documentation, coding, and releases, demonstrating measurable productivity and quality improvements.
Preferred qualifications, capabilities, and skills
- AWS (hands-on): SageMaker, Bedrock, Glue, Redshift Serverless, DynamoDB, EventBridge, Step Functions, Lambda, ECS, EKS, Kinesis, CloudWatch.
- Outside AWS: Python, Terraform, GitHub Copilot, Airflow, Kubernetes, Docker, MLflow, Datadog, Dynatrace, MCP.
- JPMC platforms/tools (highly preferred): Jules/JET, GKP (Gaia Kubernetes), Fusion MLOps.