JPMorgan Lead Site Reliability Engineer 

United States, Texas, Plano 

317916791

Job responsibilities

• Advocate and embody site reliability principles, fostering a culture of excellence and technical influence within your team.
• Leverage AI tools to enhance operational effectiveness and automate processes, ensuring high-quality customer service.
• Spearhead projects aimed at enhancing the reliability and stability of applications and platforms.
• Utilize data-driven analytics and AI technologies to automate detection, diagnosis, resolution processes, elevate service levels and drive continuous improvement.
• Engage stakeholders to establish realistic service level objectives and error budgets, ensuring alignment with customer expectations.
• Exhibit advanced technical proficiency in one or more domains, proactively addressing technology-related bottlenecks.
• Employ AI-driven solutions to streamline processes and enhance operational efficiency.
• Serve as the primary contact during major incidents, demonstrating the ability to swiftly identify and resolve issues to prevent financial losses.
• Act as a culture carrier by documenting and disseminating knowledge through internal forums and communities of practice.
• Mentor team members, guiding them in the strategic adoption of AI technologies to enhance operational effectiveness and customer service.

Required qualifications, capabilities, and skills

• Formal training or certification on site reliability engineering concepts and 5+ years applied experience.
• Proven success in an SRE or senior DevOps role, with deep knowledge of service level indicators/objectives (SLIs/SLOs), incident management, postmortem analysis, and systems reliability.
• Expert with observability stacks (e.g., Prometheus, Grafana, Splunk, OpenTelemetry), including deep experience correlating telemetry across services and time.
• Hands-on skills in coding (at least one high-level programming language), cloud platforms (AWS or GCP), container orchestration (Kubernetes), infrastructure as code (Terraform), and resilient CI/CD pipelines.
• Active experience or deep curiosity in applying AI to operations—such as LLM-based copilots, anomaly detection, automated runbooks, autonomous agents (e.g. CrewAI, LangGraph), or Retrieval-Augmented Generation (RAG) workflows for support.
• A track record of delivering under pressure. You finish what you start, adapt to uncertainty, and thrive in high-accountability environments.
• You deconstruct complexity, organize effectively, and drive clarity into ambiguous operational environments. Documentation and design are second nature.
• Outstanding communication, empathy, and professionalism—especially during incidents. You recognize that great systems serve real people.