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Sr Lead Software Engineer - Market Risk Technology SRE

JPMorgan Chase
London, GBR
Full-time
Senior · 5+ years experience
Onsite
Discovered 2 weeks ago
awsgcpgrafanajavaprometheuspython

Full Job Posting

Job responsibilities

  • Creates and delivers high quality designs, roadmaps, and program charters alongside the engineering team
  • 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 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 by understanding application and platform interdependencies and limitations
  • Provides comprehensive and ongoing guidance, tools, and solutions to support the firms’ growth
  • Make 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.

Required qualifications, capabilities, and skills

  • Formal training or certification on site reliability engineering concepts and 5+ years applied experience
  • Fluency in at least one programming language such as Python, Java.
  • Brings an advanced understanding of site reliability culture and principles and a track record of demonstrating how to implement site reliability within an application or platform
  • Advanced knowledge and experience in observability such as white and black box monitoring, service level objectives, alerting, and telemetry collection
  • 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.
  • Advanced knowledge of software applications and technical processes with considerable depth in one or more technical disciplines
  • Demonstrated ability to communicate data-based solutions with complex reporting and visualization methods
  • 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
  • Track record of automating and delivering business process improvement.

Preferred qualifications, capabilities, and skills

  • Fluency in Python
  • Familiarity with observability and monitoring tools such as Prometheus, Grafana, or OpenTelemtry
  • Familiarity with cloud technologies such as AWS or GCP, including deployment, management, and optimization of cloud-based applications
  • Experience working in the financial/fintech industry

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