Site Reliability Engineer III - Machine Learning

Company : Jpmorgan Chase

Job Description - Site Reliability Engineer III - Machine Learning

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 Corporate Technology, Consumer & Community Banking Risk team, you will tackle complex, wide‑ranging business challenges by designing and implementing clear, efficient technical solutions. You will use code and cloud infrastructure to configure, maintain, monitor, and optimize applications and their underlying platforms, independently decomposing existing systems and iteratively enhancing them. In this role, you are a key contributor to your team, sharing deep expertise in end‑to‑end operations, availability, reliability, and scalability to ensure the resilience and performance of critical applications and services.

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.
Implements infrastructure, configuration, and network as code for the applications and platforms in your remit
Collaborates with technical experts, key stakeholders, and team members to resolve complex problems and proactively address issues using service level indicators and objectives before they impact customers
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.
Familiar with availability, reliability, scalability, and solutions in their applications and works with partners to improve these outcomes iteratively
Proactively recognizes road blocks and identifies improvements to solve business problems, including exploring new technologies where appropriate

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.)
Experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection
Experience with continuous integration and continuous delivery tooling
Familiarity with container and container orchestration and troubleshooting common networking technologies and issues

Preferred qualifications, capabilities, and skills

• Experience orchestrating data/compute workflows (e.g., Airflow or AWS Step Functions).
  • Familiarity with Databricks jobs, clusters, and workspace operations (experience using Python or REST APIs to interact is a plus).
  • Infrastructure-as-Code experience; Terraform Enterprise exposure preferred.
  • GitOps and configuration management exposure (e.g., Argo CD/Flux patterns), and operational readiness automation tied to pull-request workflows.
  •Familiarity with OpenTelemetry or similar standards for metrics/logs/traces instrumentation and correlation.
  • AWS certification preferred.

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Site Reliability Engineer III - Machine Learning

Job Description - Site Reliability Engineer III - Machine Learning

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