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

As a Software Engineer at JPMorgan Chase within the Commercial and Investment Bank, you will partner with Data Scientists to create cloud‑based frameworks for hosting and operating models, applying SDLC and MLOps best practices to ensure reliability, security, and performance. You will leverage both internal and public cloud platforms with a mix of proprietary and open‑source tools, collaborating closely with platform developers and engineering communities to integrate and evolve existing and new technologies

Job responsibilities

• Develop and maintain secure, high-quality applications using Python and AWS
• Produce architecture and design deliverables; contribute to solution design and reviews
• Integrate AI/ML solutions into complex, domain-specific processing systems
• Participate in code reviews, design discussions, and agile planning ceremonies
• Collaborate with SRE and monitoring teams to ensure reliability, performance, and observability
• Contribute to engineering communities of practice and technology events
• Embrace continuous learning and creative problem-solving with a can-do mindset

Required qualifications, capabilities, and skills

• Formal training in software engineering concepts and 3+ years of 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): Glue, Event Bridge, Step Functions, Lambda, ECS, EKS, Kinesis, CloudWatch
• Outside AWS: Python, Terraform, Tiger Graph, graph databases, GitHub Copilot, Airflow, Kubernetes
• JPMC platforms/tools (highly preferred): Jules/JET, GKP (Gaia Kubernetes), Fusion MLOps