Leads AWS cloud architecture and site reliability engineering for business-critical production services. Defines SLI/SLO practices, error budgets, observability, capacity planning, incident response, and production readiness standards. Drives root-cause analysis, durable remediation, cloud cost optimization, automation, and operational risk reduction across engineering teams. Promotes responsible use of approved AI-assisted development tools while ensuring correctness, security, resiliency, and compliance.
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Senior Software Engineer at JPMorgan Chase within the Consumer and community banking technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.
Job Responsibilities
- Dive into Live Site Management and cloud production management practices, including production readiness, change governance, incident response, problem management, and operational risk reduction.
- Define and improve SRE practices, including service-level indicators, service-level objectives, error budgets, capacity planning, and reliability engineering.
- Advance observability across applications and infrastructure through effective logging, metrics, distributed tracing, dashboards, alerting, and automated anomaly detection.
- Drive major incident response, root-cause analysis, corrective actions, and the systematic elimination of recurring production issues.
- Establish production health, availability, performance, and resiliency measures that provide actionable insight to engineering and business leadership.
- Promote team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes, while establishing consistent validation standards and promoting reuse of effective patterns across the team.
- Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized through automation.
- Shape the end-to-end AWS cloud architecture strategy across all product components.
- Strengthen cloud cost strategy and optimization across the product.
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and 5+ years applied experience
- Deep, broad AWS expertise across compute, data, networking, security, and observability, with proven production architecture experience.
- Systems thinking, including the ability to reason about trade-offs, failure modes, and dependencies across an entire product.
- Strategic command of cost, scalability, automation, reliability, and AI integration as connected levers.
- Hands-on depth to validate and prototype ideas, not just advise.
- Proven experience managing cloud-hosted production services and leading Live Site Management practices in complex, business-critical environments.
- Strong SRE and observability expertise, including SLI/SLO definition, error budgets, telemetry, distributed tracing, alert design, capacity management, and performance engineering.
- Demonstrated ability to lead high-severity incident response, perform root-cause analysis, and drive durable remediation across multiple engineering teams.
- Experience establishing production readiness standards, operational controls, runbooks, dashboards, and measurable service health objectives.
- Demonstrated experience leading effective use of approved AI-assisted software development tools, with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices.
JPMorganChase Mumbai, Maharashtra, IND Office
B11, B9, B10, Nirlon Knowledge Park, near Mrinal Tai Gore Flyover, Cama Industrial Estate, Mumbai, Maharashtra, India, 400063
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