JPMorgan Lead Site Reliability Engineer United States, Texas, Plano 978643534
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Assume a critical role in defining the future of a globally recognized firm and have a direct and significant effect in a realm tailored for top achievers in site reliability.
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-promoten analytics and AI technologies to automate detection, diagnosis, resolution processes, elevate service levels and promote 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-promoten 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.
Preferred qualifications, capabilities, and skills
Experience with operational and compliance rigor in banking, fintech, or similar.
Practical use of LLM frameworks (e.g. LangChain, Semantic Kernel), AI orchestration tools, vector databases, or custom agents supporting reliability workflows.
Experience with game days, chaos experiments, or failure-mode analysis to improve service robustness.
A background in mentoring engineers or leading technical knowledge-sharing, especially around AI and SRE best practices.
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