Principal Site Reliability Engineer

Job responsibilities

• Identifies and solves problems of high complexity.
• Works with development teams throughout the Software Development Life Cycle to ensure sustainable software releases
• Leads medium to large projects by bringing together the proper perspective, identifying roadblocks, and integrating feedback from team members and subject matter experts at the firm.
• Uses enterprise-authorized AI capabilities within the work environment to accelerate complex incident analysis and reliability decisioning, validating outputs and handling operational data according to sensitivity and security requirements.
• Manages complex business challenges with elegant, efficient solutions, harnessing the power of code and cloud infrastructure to configure, maintain, monitor, and optimize applications, driving continuous improvement and scalability.
• Lead the design and development of core observability services, including metrics pipelines and log aggregation.
• Leverage modern technologies such as Open Telemetry and AI/ML for anomaly detection and automated insights.
• Collaborate with engineering and SRE teams to define service-level objectives (SLOs) and error budgets.
• Provide technical leadership and mentorship to engineering teams, ensuring best practices in system design.
• Champion observability as a first-class concern in the software development lifecycle.
• Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices, ensuring traceability/auditability, resiliency, and security controls.

Required qualifications, capabilities, and skills

• Formal training or certification on Site Reliability Engineering concepts and 10+ years applied experience
• Fluent in at least one programming language such as: Python, Java/Spring Boot.
• Experience with cloud-native (AWS) instrumentation and streaming data platforms.
• Proficient with continuous integration and continuous delivery tools like Jenkins, GitLab, or Terraform
• Proficient with container and container orchestration: (ECS, Kubernetes, Docker).
• 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 validate AI-assisted operational recommendations before applying changes, escalating when uncertain and following data sensitivity requirements.
• Experience with translating research, analysis, and tests into business recommendations.
• Ability to balance and be accountable for the work of multiple architects and designers.
• Understands and leads partnerships across job functions to develop efficient systems.
• Engages team members and expresses complex ideas with appropriate level of detail, while providing constructive feedback.

Preferred qualifications, capabilities, and skills

• Influence technology and policy decisions while fostering commitment and confidence in team members.
• Develop effective solutions and analyze competitive positions by considering market trends.
• Support the introduction of innovative methods and communicate clearly to persuade audiences.
• Demonstrate concern and meet the needs of both internal and external customers.