Senior Lead Site Reliability Engineer - AI/ML and Data Platforms at JPMC Candidate Experience page

Jersey City, New Jersey, United States -

Full Time

Start Date

Immediate

Expiry Date

11 Sep, 26

Salary

260000.0

Posted On

13 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Site Reliability Engineering, Observability, SLI/SLO/SLA, Distributed Systems, AI/ML Platforms, Data Lake Ecosystems, Grafana, Dynatrace, Prometheus, Datadog, Splunk, AWS, Databricks, Spark, Kubernetes, Terraform

Industry

Financial Services

Description

Elevate your engineering prowess to unprecedented levels by joining a team of exceptionally gifted professionals and position yourself among the top echelon in site reliability. As a Senior Lead Site Reliability Engineer at JPMorgan Chase within the Chief Data & Analytics Office (CDAO) AI/ML & Data Platforms team, you work with your fellow stakeholders to define non-functional requirements (NFRs) and availability targets for services supporting large-scale data platforms and data lake ecosystems. You will ensure those NFRs are embedded into product design and testing phases, that service level indicators effectively measure customer and data platform performance, and that service level objectives are defined with stakeholders and implemented in production to support secure, scalable, and high-performing analytics and AI/ML workloads. Job responsibilities * Creates and delivers high quality designs, roadmaps, and program charters alongside the engineering teams, including data platform and distributed systems initiatives * Acts as a key resource and mentor for technologists in your area seeking advice on technical and business issues, and serves as a culture carrier and site reliability adoption champion for your team * Collaborates with others to create and implement observability and reliability designs for complex systems and data platforms which are robust, stable, and do not incur additional toil or technical debt * Uses enterprise-authorized AI capabilities within the work environment to accelerate reliability design and operational decisioning (e.g., incident/post-incident analysis and requirements traceability), validating outputs and handling operational data according to sensitivity and security requirements * Drives evolution and debugging of critical components, including platform and data system dependencies, by understanding application and infrastructure interdependencies and limitations * Provides comprehensive and ongoing guidance, tools, and solutions to support the firm’s growth, including scalable data platform infrastructure and engineering best practices * Makes significant contributions to JPMorganChase’s site reliability community via internal forums, communities of practice, guilds, and conferences * Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., testing/validation automation and production readiness), ensuring traceability/auditability, resiliency, and security controls across application and data platform environments Required qualifications, capabilities, and skills * Formal training or certification on site reliability engineering concepts and 5+ years applied experience * Brings an advanced understanding of site reliability culture and principles and a track record of demonstrating how to implement site reliability within applications, platforms, or large-scale data systems, including strong understanding of SLI/SLO/SLA and error budgets * Advanced knowledge and experience in observability such as white and black box monitoring, service level objectives, alerting, and telemetry collection across distributed and data platform environments, including tools such as Grafana, Dynatrace, Prometheus, Datadog, and Splunk * Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve reliability engineering workflows with strong validation habits and awareness of data sensitivity * Ability to set team practices for safe AI usage in operations (e.g., review/approval expectations and escalation paths) while maintaining resiliency, security, and auditability outcomes, ensuring compliance with risk controls and company-wide standards * Advanced knowledge of software applications and technical processes, including distributed systems, system design, resiliency, testing, operational stability, and disaster recovery, with considerable depth in one or more technical disciplines * Demonstrated ability to communicate data-based solutions with complex reporting and visualization methods and collaborate effectively across teams to drive incident resolution and improvements * Recognized as an active contributor of the engineering community * Strong communication skills and a desire to mentor and educate others on site reliability engineering principles and practices while building strong cross-functional relationships Preferred qualifications, capabilities, and skills * Experience with AWS platforms and managed data platforms such as Databricks, including platform administration and engineering support * Experience in building and managing data pipelines using Spark or similar distributed compute frameworks * Familiarity with big data ecosystem tools (e.g., Spark, Glue, MapReduce) * Knowledge of containerization (Docker, Kubernetes) and orchestration frameworks * Experience with CI/CD pipelines, automation frameworks, and infrastructure as code (e.g., Terraform) * Proficiency in Python or similar programming languages for automation and platform development * Familiarity with large-scale distributed systems and data processing environments JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 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 [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Responsibilities

Define non-functional requirements and availability targets for large-scale data platforms and AI/ML workloads. Lead the design and implementation of observability and reliability workflows while mentoring other technologists.