As a Lead Site Reliability Engineer at JPMorgan Chase within Market Risk Technology, you hold a leadership role in your team, demonstrate strong knowledge across multiple technical domains, and advise others on the technical and business issues facing them. Take lead and conduct resiliency design reviews, break up complex problems into digestible work for other engineers, act as a technical lead for medium to large-sized products, and provide advice and mentoring to other engineers.
Job responsibilities
- Demonstrates and champions site reliability culture and practices and exerts technical influence throughout your team
- Leads initiatives to improve the reliability and stability of your team’s applications and platforms using data-driven analytics to improve service levels
- Collaborates with team members to identify comprehensive service level indicators and stakeholders to establish reasonable service level objectives and error budgets with customers
- Uses enterprise-authorized AI capabilities within the work environment to accelerate major-incident triage, troubleshooting, and post-incident analysis, validating outputs and handling operational data according to sensitivity and security requirements.
- Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., CI/CD quality checks, test/validation automation, and operational readiness), ensuring traceability/auditability, resiliency, and security controls.
- Demonstrates a high level of technical expertise within one or more technical domains and proactively identifies and solves technology-related bottlenecks in your areas of expertise
- Acts as the main point of contact during major incidents for your application and demonstrates the skills to identify and solve issues quickly to avoid financial losses
- Documents and shares knowledge within your organization via internal forums and communities of practice
Required qualifications, capabilities, and skills
- Formal training or certification in software engineering concepts with 5+ years of applied experience.
- Deep proficiency in reliability, scalability, performance, security, enterprise system architecture, toil reduction, and other site reliability best practices with the ability to implement these practices within an application or platform
- Fluency in at least one programming language such as (e.g., Python, Java Spring Boot, .Net, etc.)
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve SRE workflows (e.g., incident investigation support and knowledge capture) with strong validation habits and awareness of data sensitivity.
- Ability to evaluate AI-assisted operational recommendations for correctness and risk, define appropriate guardrails for team usage, and ensure outcomes align to resiliency and security expectations.
- Deep knowledge of software applications and technical processes with emerging depth in one or more technical disciplines
- Proficiency and experience in observability such as white and black box monitoring, SLO alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
- Proficiency in continuous integration and continuous delivery tools (e.g., Jenkins, GitLab, Terraform, etc.)
- Experience with container and container orchestration (e.g., ECS, Kubernetes, Docker, etc.)
- Experience with troubleshooting common technologies and issues
- Ability to identify and solve problems related to complex data structures and algorithms
Drive to self-educate and evaluate new technology
Preferred qualifications, capabilities, and skills
- Ability to teach new programming languages to team members
- Ability to expand and collaborate across different levels and stakeholder groups