Intro marketing language
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.
Job summary
As a Software Engineer III at JPMorganChase within the CONSUMER & COMMUNITY BANKING, 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'll help build and operate resilient AWS cloud platforms, contribute to automation and observability, and support AI/ML-enabled capabilities that improve operational efficiency and customer outcomes.
Job responsibilities
- Execute software solutions across design, development, and production troubleshooting for cloud-based platforms, participating in design discussions and technical reviews.
- Develop and maintain AWS infrastructure (e.g., EC2, S3, RDS, CloudWatch, EKS) using Infrastructure-as-Code and automation to advance self-service capabilities.
- Support end-to-end incident and problem management for public cloud environments, helping diagnose and resolve production issues to maintain availability and minimize downtime.
- Improve resiliency, performance, and security by identifying risks/patterns, optimizing operational tasks, and enhancing monitoring and alerting.
- Analyze upcoming platform-level changes prior to release and communicate impacts clearly to stakeholders to support safe delivery.
- Contribute to operational readiness activities (e.g., game days, resiliency testing, chaos exercises) and continuous process improvements that reduce time to resolve incidents.
- Build AI/ML-enabled features (e.g., automation pipelines, intelligent monitoring, data-driven platform capabilities) and contribute to engineering communities of practice.
Required qualifications, capabilities, and skills
- Formal training or certification in software engineering concepts and 3+ years of applied experience, including hands-on experience supporting or building AWS environments using Infrastructure-as-Code (e.g., Terraform or CloudFormation).
- Hands-on practical experience in system design, application development, testing, and operational stability in cloud or platform environments.
- Proficient in coding in one or more languages (e.g., Python) and experience developing, debugging, and maintaining code in a large corporate environment.
- Overall knowledge of the Software Development Life Cycle and solid understanding of agile practices such as CI/CD, application resiliency, and security.
- Experience with container technologies (Docker and Kubernetes) and operating containerized workloads in a cloud environment.
- Experience with monitoring/observability and troubleshooting (e.g., CloudWatch, Prometheus, Splunk, Dynatrace) and familiarity with incident/problem management practices.
- Demonstrated knowledge in a relevant technical discipline such as cloud, artificial intelligence, or machine learning (including exposure to ML/GenAI concepts and production deployment considerations).
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies.
- Exposure to additional cloud technologies and services beyond core AWS (e.g., multi-account strategies, advanced networking, edge/CDN patterns).
- Experience with MLOps tooling (e.g., MLflow or Weights & Biases), LLM frameworks (e.g., LangChain or LlamaIndex), and/or vector databases used for retrieval workflows.
- Exposure to AWS AI services (e.g., SageMaker) and responsible AI practices (e.g., explainability, bias testing) in regulated environments.
