Lead design and implement reliability, scalability, and observability for cloud and data platforms. Build IaC, CI/CD pipelines, use monitoring and SLO-driven improvements, apply enterprise AI for incident triage and reliability insights, and collaborate across teams to reduce toil and improve operational outcomes.
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 Senior Lead Site Reliability Engineer at JPMorgan Chase within the Infrastructure Data Platform 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.
- 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 advanced 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, while ensuring compliance with risk controls and company-wide standards
- Proficient knowledge of software applications and technical processes within a given technical discipline (e.g., Cloud, AI & etc.)
- Hands-on experience supporting cloud and data platforms, including AWS (e.g., EC2, Athena) and Snowflake, with a reliability-first mindset
- Experience in observability such as white and black box monitoring, service level objective alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, AppDynamics, and others
- Experience with continuous integration and continuous delivery tooling (e.g., Jenkins, GitLab, Terraform)
- Familiarity with container and container orchestration and troubleshooting common networking technologies and issues (e.g., Docker, Kubernetes, ECS)
Preferred qualifications, capabilities, and skills
- Strong understanding of release engineering practices, GitOps, branching strategies, and change management discipline
- Experience with incident management, on-call operations, capacity planning, and reliability engineering practices
- Experience authoring pipeline configuration (for example, YAML) and infrastructure templates (for example, Terraform or ARM)
- Demonstrated ability to assess risk, remain calm under pressure, and drive clear
- AWS and Azure experience preferred; Oracle Cloud Infrastructure (OCI) exposure is a plus
About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorganChase London, England Office
25 Bank Street, Canary Wharf, London, United Kingdom, E14 5JP
Similar Jobs
Financial Services
Lead enterprise architecture for Digital Workflows, managing multiple teams and cross-product initiatives. Drive ServiceNow adoption, provide strategic direction, interface with senior stakeholders, and deliver firmwide architecture objectives while championing inclusion.
Top Skills:
Data WarehouseDatabaseJavaServicenow
Financial Services
Design, develop, and maintain scalable ELT data pipelines on Databricks/Palmos using Python, Spark/PySpark and SQL. Onboard enterprise datasets, apply CI/CD and testing, implement data governance and security, optimize performance, and support analytics and AI/ML use cases while leveraging enterprise AI-assisted development tools.
Top Skills:
Ai-Assisted Development ToolsAWSCi/CdDatabricksNoSQLPalmosPysparkPythonSparkSQL
Financial Services
Lead and mentor SRE practices to design, implement, and operate reliable cloud and data platforms. Build IaC, CI/CD, observability, and containerized deployments; use enterprise AI to accelerate incident triage and reliability improvements while ensuring compliance and data sensitivity controls.
Top Skills:
.NetAppdynamicsArmAthenaAws Ec2AzureDatadogDockerDynatraceEcsEnterprise AiGitlabGitopsGrafanaJavaJenkinsKubernetesOracle Cloud InfrastructurePrometheusPythonSnowflakeSplunkSpring BootTerraformYaml
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
