
Lead Site Reliability Engineer, AI/ML Platform
at J.P. Morgan
Posted a month ago
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- Compensation
- Not specified
- City
- Jersey City
- Country
- United States
Currency: Not specified
Lead SRE for AI/ML platform responsible for designing and implementing solutions to improve reliability, scalability, and performance of AI/ML systems. Partner with product engineering teams to build observability, security, automation, and fin-ops tooling, and define reliability and automation architecture standards. Own production incident debugging, participate in on-call rotations, and mentor junior engineers while driving cross-functional engagements. Provide strategic technical leadership to ensure cloud-native, distributed system reliability at scale.
Location: Jersey City, NJ, United States
Responsibilities:
- Design and implement solutions to enhance the reliability and scalability of AI/ML platforms and applications to accommodate fast growing demands.
- Partner with product engineering teams to ensure the AI/ML systems are reliable and high performing.
- Develop observability, security, automation and fin-ops tools and orchestration.
- Provide strategic technology leadership by defining and evaluating standards and architecture for reliability, observability and automation frameworks.
- Build strong cross-functional relationships that foster engagements across the organization and deliver solutions to user problems.
- Debug and solve issues in a production environment, identify root cause and remediate.
- Participates in on-call rotations, incident management and escalation workflows.
- Take full ownership of problems, develop solutions, and acquire new knowledge to complete the task.
- Mentor and guide junior engineers.
Required Qualifications:
- Bachelor’s degree in computer science, Information Technology, or equivalent technical qualification with 5+ years professional experience.
- Expertise in SRE principles, reliability, scalability and performance of application and infrastructure.
- Have hands-on experience with cloud platforms (AWS, GCP, Azure) and IaC tools (Terraform, Ansible).
- Extensive experience implementing advanced observability using tools like Open Telemetry, Dynatrace, Grafana, and/or cloud-native services.
- Experience in architecting distributed systems and cloud-native architecture in AWS.
- Systematic problem-solving and troubleshooting skills in a complex system.
- Excellent communication skills and ability to represent and present business and technical concepts to stakeholders.
- Self-managed, self-motivated with strong sense of ownership, urgency, and drive
Good to have:
- Prior experience working in AI, ML, or Data engineering.
- Prior experience developing AI Ops/AI Agents.
- Multi cloud experience (AWS, GCP, Azure) is a plus




