Site Reliability Engineer III

JPMorganChase • Tampa, FL

1d

About The Position

As a Site Reliability Engineer III at JPMorganChase within the Commercial & Investment Bank — Payments Technology team, you will work on platforms that move money globally, where reliability, security, and performance are essential. You will solve complex business problems through code and cloud infrastructure, configuring, maintaining, monitoring, and optimizing highly available, low-latency payment processing platforms and their associated infrastructure. You will contribute to the team by sharing end-to-end operational expertise in availability, reliability, and scalability, and by helping raise the bar for the team.

Requirements

• Formal training or certification in site reliability engineering concepts and at least 3 years of applied experience.
• Proficiency in site reliability culture and principles, with familiarity implementing site reliability practices within an application or platform.
• Proficiency in at least one programming language, such as Python, Java/Spring Boot, or .NET.
• Experience with observability practices, including white- and black-box monitoring, service level objective alerting, and telemetry collection.
• Experience with continuous integration and continuous delivery tooling.
• Proficient knowledge of software applications and technical processes within a technical discipline such as cloud, AI, or distributed systems.
• Familiarity with containers, container orchestration, and troubleshooting common networking technologies and issues.
• Working knowledge of enterprise-authorized AI capabilities for site reliability engineering workflows, with strong validation habits and awareness of data sensitivity.
• Ability to validate AI-assisted operational recommendations before applying changes, escalate when uncertain, and adhere to data sensitivity requirements.

Nice To Haves

• Experience supporting highly available, secure, low-latency payment processing platforms in financial services, including familiarity with fraud screening or payment flow patterns.
• Hands-on experience with Kafka and event-driven data ingestion pipelines, and working knowledge of AI agentic models and MCP-based frameworks applied to reliability use cases.
• Proficiency with OpenTelemetry, Grafana, Splunk, or Dynatrace, with a track record of improving reliability through monitoring, incident response, and automation.
• Experience implementing service level objective programs, performance testing, capacity planning, and resilience testing, including fault injection, chaos engineering, and disaster recovery exercises.
• Experience improving operational maturity through standardized runbooks, automated health checks, auto-remediation, and deployment guardrails.
• Familiarity with database reliability patterns, including capacity management, backup strategies, and failover readiness, as well as secure operational practices such as least privilege and secrets handling.

Responsibilities

• Guide and assist teammates in building appropriate-level designs, reaching peer consensus, and adopting site reliability engineering best practices.
• Collaborate with software engineers and cross-functional teams to design, develop, test, and implement deployment and reliability approaches using automated continuous integration and continuous delivery pipelines.
• Implement infrastructure, configuration, and network as code for payment processing applications and platforms, ensuring consistency, repeatability, and auditability.
• Monitor and maintain Kafka-based data ingestion pipelines to support the reliability and throughput of high-availability, low-latency payment flows.
• Collaborate with technical experts, stakeholders, and team members to resolve complex problems and proactively address issues using service level indicators and objectives before they affect customers.
• Implement and improve observability solutions, including OpenTelemetry, Grafana, Splunk, and Dynatrace, to improve transparency, incident response, and measurable service level objective outcomes.
• Apply enterprise-authorized AI capabilities to identify operational signal patterns indicating reliability risk or recurring toil, prioritizing reuse-first improvements tied to service level objective outcomes.
• Use enterprise-authorized AI capabilities to accelerate incident triage, troubleshooting, and post-incident analysis; validate outputs and handle operational data according to security and sensitivity requirements.
• Identify roadblocks and drive improvements to solve business problems, including exploring AI agentic models and MCP-based frameworks where appropriate.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed