At JPMorgan Chase, the Chief Data Analytics Office (CDAO) is looking to drive strategic investments in AI/ML and data-oriented tools and capabilities, and the Platform Engineering team is at the forefront of building innovative platforms, automating infrastructure operations, and enabling Agentic-based AIOps platforms to enhance scalability, security, and reliability for CDAO-hosted managed services.
Requirements
- Hands-on experience with one or more cloud computing platform providers AWS/Azure/GCP
- Advanced knowledge of Containerization and Container Runtime/Orchestration platforms (Docker/Kubernetes/ECS etc.)
- Hands-on experience with Cloud Infrastructure Provisioning Tools like Terraform, Pulumi, Crossplane etc.
- Proficiency with programming languages like Golang/Python and understand software development best practices
- Hands-on experience with CI/CD/SCM tools like Jenkins, Spinnaker, Bitbucket/Github etc. and with logging and monitoring tools Splunk, Grafana, Datadog, Prometheus etc.
- Deep understanding of cloud infrastructure design, architecture and cloud migration strategies
- Strong knowledge of cloud security best practices, shift left methodologies and DevSecOps processes
Responsibilities
- Provide technical leadership and guidance to the cloud engineering team
- Lead the design and development of the cloud infrastructure offerings and platform tools, ensuring that they are secure, scalable, and reliable
- Develop secure and high-quality production code, perform code reviews and debug issues
- Analyze performance characteristics of systems across our platform and improve resiliency and security posture
- Design and develop scalable AIOps solutions to support AI/ML and Data Platforms
- Implement data pipelines and workflows to collect, process, and analyze large volumes of platform data in real-time
- Ensure the reliability, availability, and performance of the AIOps platform through effective monitoring and maintenance
Other
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Bachelor’s degree in Computer Science, Data Engineering, or a related field.
- Proven experience in platform engineering, with a focus on AI/ML technologies and IT operations
- Master's degree in a related field (preferred)
- Experience leading end-end platform development efforts (preferred)
