This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.
As a Manager of Software Engineering at JPMorgan Chase within the AI/ML & Data Platform team, you lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team's work adheres to compliance standards, business requirements, and tactical best practices.
Job responsibilities
- Oversee and guide a team of software engineers dedicated to developing tools for observability, data pipelines, financial operations, and orchestration.
- Collaborate with customers, product managers, and Site Reliability Engineering (SRE) teams to create systems and synchronize observability goals throughout the organization.
- Offer architectural guidance and set standards for observability implementations, emphasizing cost efficiency and compliance.
- Work with cross-functional teams to enhance business impact and ensure customer satisfaction through outstanding software delivery.
- Assess and adopt modern data storage solutions, such as data warehouses and data lakes, to facilitate advanced analytics and dashboard capabilities.
- Implement best practices for data transformation, real-time processing, and modern data storage solutions to support advanced analytics.
- Review and integrate new observability tools and technologies, keeping abreast of industry best practices.
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Required qualifications, capabilities, and skills
- Formal training or certification on Software engineering concepts and 5+ years applied experience
- Experience in managing people and leading technical teams.
- Hands-on experience in backend development using languages such as Python, Java, Node.js, or Golang.
- Experience working as an Infrastructure or Platform Software Engineer in a fast-paced technology company or startup.
- Proficiency in cloud-native observability tools, including OpenTelemetry, Grafana, Prometheus, CloudWatch, Datadog, and related agents and collectors.
- Experience in designing and architecting large-scale distributed systems and cloud-native architecture on AWS.
- Excellent communication skills with the ability to convey and present business and technical concepts to stakeholders.
Preferred qualifications, capabilities, and skills
- Familiarity working in AI, ML, or Data engineering.
- Familiar with developing Automation frameworks/AI Ops