Site Reliability Engineer III- Production Management

JPMorgan Chase & Co.; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. in New York is seeking a Site Reliability Engineer III to advance availability, reliability, and scalability of critical systems.

You will work across production management teams, build and monitor cloud-based services, and drive incident response with automated CI/CD and AI-assisted tooling. This role emphasizes hands-on coding (Python/Java/.NET) and collaboration with software engineers to improve observability and resilience.

Qualifications

• Formal training or certification on site reliability engineering concepts and 3+ years applied experience.
• Proficient in site reliability culture and principles and familiarity with how to implement site reliability within an application or platform.
• Proficient in at least one programming language such as Python, Java/Spring Boot, and .Net
• Working knowledge of using enterprise‑authorized AI capabilities within the work environment to support SRE workflows with strong validation habits and awareness of data sensitivity
• Ability to validate AI‑assisted operational recommendations before applying changes, escalating when uncertain and following data sensitivity requirements
• Practical cloud experience in AWS supporting production services (visibility/troubleshooting, deployments, and operational hygiene)
• Ability to write code to automate support work (e.g., Python, Java, or similar) and reduce operational toil
• Experience operating in time‑sensitive environments (market hours or similar), with strong incident discipline and stakeholder communication
• Strong debugging fundamentals across distributed systems (logs/metrics, latency analysis, dependency failures, data issues)

Responsibilities

• Guides and assists others in the areas of building appropriate level designs and gaining consensus from peers where appropriate, supporting adoption of site reliability engineering best practices within your team
• Collaborates with other software engineers and teams to design, develop, test, and implement deployment and reliability approaches using automated continuous integration and continuous delivery pipelines
• Uses enterprise‑authorized AI capabilities within the work environment to accelerate incident triage, troubleshooting, and post‑incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.
• Continuously monitor operational signals (alerts, dashboards, service health indicators, and desk/user feedback) and drive rapid engagement, ownership, and coordination when issues emerge
• Enhance production observability and reliability by improving instrumentation, dashboards, and alert quality; use trend and incident data to reduce noise, prevent recurrence, and measurably lower MTTR and incident frequency
• Own and improve the support operating model: maintain/run runbooks, ensure clean handoffs and escalation paths, manage shift coverage, and drive disciplined post‑incident follow‑through (actions, owners, due dates)
• Partner with engineering and adjacent service owners to drive root‑cause fixes and stronger change/release standards, identify cross‑service dependencies early, and build lightweight automation/self‑service tooling to reduce manual steps and speed repeatable triage
• Lead L1/L2 production support using SRE practices: quickly triage incidents, investigate likely causes, apply safe mitigations/workarounds, and provide timely, clear stakeholder updates through to resolution
• Applies enterprise‑authorized AI capabilities within the work environment to identify patterns in operational signals that indicate reliability risk or recurring toil, prioritizing reuse‑first improvements tied to SLO outcomes.

Skills

SRE fundamentals

Python

Java / Spring Boot

.NET

Cloud AWS

Incident management

Automate with code

Debugging distributed systems

Time-sensitive environments

Tools

Datadog

Kafka

CI/CD tooling

Job description

There’s nothing more exciting than being at the center of a rapidly growing field in technology and applying your skillsets to drive innovation and modernize the world's most complex and mission‑critical systems.

As a Site Reliability Engineer III at JPMorgan Chase within the Commercial & Investment Bank, Production management team, you will solve complex and broad business problems with simple and straightforward solutions. Through code and cloud infrastructure, you will configure, maintain, monitor, and optimize applications and their associated infrastructure to independently decompose and iteratively improve on existing solutions. You are a significant contributor to your team by sharing your knowledge of end‑to‑end operations, availability, reliability, and scalability of your application or platform.

Job Responsibilities

• Guides and assists others in the areas of building appropriate level designs and gaining consensus from peers where appropriate, supporting adoption of site reliability engineering best practices within your team
• Collaborates with other software engineers and teams to design, develop, test, and implement deployment and reliability approaches using automated continuous integration and continuous delivery pipelines
• Uses enterprise‑authorized AI capabilities within the work environment to accelerate incident triage, troubleshooting, and post‑incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.
• Continuously monitor operational signals (alerts, dashboards, service health indicators, and desk/user feedback) and drive rapid engagement, ownership, and coordination when issues emerge
• Enhance production observability and reliability by improving instrumentation, dashboards, and alert quality; use trend and incident data to reduce noise, prevent recurrence, and measurably lower MTTR and incident frequency
• Own and improve the support operating model: maintain/run runbooks, ensure clean handoffs and escalation paths, manage shift coverage, and drive disciplined post‑incident follow‑through (actions, owners, due dates)
• Partner with engineering and adjacent service owners to drive root‑cause fixes and stronger change/release standards, identify cross‑service dependencies early, and build lightweight automation/self‑service tooling to reduce manual steps and speed repeatable triage
• Lead L1/L2 production support using SRE practices: quickly triage incidents, investigate likely causes, apply safe mitigations/workarounds, and provide timely, clear stakeholder updates through to resolution
• Applies enterprise‑authorized AI capabilities within the work environment to identify patterns in operational signals that indicate reliability risk or recurring toil, prioritizing reuse‑first improvements tied to SLO outcomes.

Required qualifications, capabilities, and skills

• Formal training or certification on site reliability engineering concepts and 3+ years applied experience
• Proficient in site reliability culture and principles and familiarity with how to implement site reliability within an application or platform
• Proficient in at least one programming language such as Python, Java/Spring Boot, and .Net
• Working knowledge of using enterprise‑authorized AI capabilities within the work environment to support SRE workflows with strong validation habits and awareness of data sensitivity
• Ability to validate AI‑assisted operational recommendations before applying changes, escalating when uncertain and following data sensitivity requirements
• Proficient knowledge of software applications and technical processes within a given technical discipline (e.g., Cloud, AI, Android, etc.)
• Practical cloud experience in AWS supporting production services (visibility/troubleshooting, deployments, and operational hygiene)
• Ability to write code to automate support work (e.g., Python, Java, or similar) and reduce operational toil
• Experience operating in time‑sensitive environments (market hours or similar), with strong incident discipline and stakeholder communication
• Strong debugging fundamentals across distributed systems (logs/metrics, latency analysis, dependency failures, data issues)

Preferred qualifications, capabilities, and skills

• Prior Markets experience, especially pricing / risk / market data support (Fixed Income a plus)
• Experience with Datadog (metrics/logs/traces), alert tuning, dashboards, and basic SLO concepts
• Familiarity with messaging/streaming patterns (Kafka/MQ) and data quality checks in execution and pricing pipelines
• Experience applying AI‑assisted tooling to reduce support toil