Lead Site Reliability Engineer Market Risk

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 teams 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 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