Site Reliability Engineer

Total Number of Openings

1

Chevron GBS is looking for a Site Reliability Engineer (SRE) with strong expertise in observability, Azure platform services, and AI-driven engineering to primarily support our Payments reliability & Order to Cash reliability. This role focuses on building end-to-end observability solutions using Azure Monitor, ADX (KQL), and Grafana, translating telemetry into business-impact insights, and defining SLIs/SLOs and alerting strategies.

Key Responsibilities

• Drive Reliability: Define, implement, and monitor Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Error Budgets specifically tailored to mission-critical payment workflows.
• End-to-End Observability: Architect, deploy, and maintain scalable observability stacks to establish clear visibility across complex, distributed environments.
• Incident Management & Prevention: Work within a vendor-driven Operation team to reduce incidents and response times and facilitate blameless Root Cause Analysis (RCA) to permanently eliminate observability blind spots.
• Toil Elimination: Identify repetitive manual tasks and develop robust automation and self-healing mechanisms.
• AI Integration: Design and implement AI-assisted solutions, automated diagnostics, and smart alerting to accelerate incident resolution and proactively detect anomalies.
• Capacity & Performance Tuning: Monitor system health continuously to assist with load testing, capacity planning, and performance optimization.

Required Qualifications

• Proven SRE Expertise: Strong background in production reliability, modern incident response, and system architecture.
• Development & Automation Skills: Hands-on proficiency in Python, PowerShell, and C# (or another backend language). Experience with Infrastructure as Code (IaC) and CI/CD pipelines is heavily preferred.
• Advanced Telemetry Analysis: Deep experience with dashboarding (Grafana) and log analysis (ADX/KQL). Ability to validate telemetry accuracy (latency, failures, data delays) and rigorously challenge misleading signals or noisy alerts.
• Cross-Functional Collaboration: Strong communication skills with the ability to work seamlessly with engineering teams to fix code-level issues, and with business stakeholders to translate technical metrics into business impacts.
• AI Proficiency: Practical experience using AI tools (e.g., M365, GitHub Copilot) and building AI agents to scale productivity and improve data quality.

The Mindset

We are looking for someone who can analyze, question, and improve data, not just visualize it—leveraging AI to accelerate development, detect gaps, and enhance observability at scale. The successful candidate combines hands-on coding with strong analytical thinking, can navigate smoothly between engineering and business contexts, and uses AI to scale productivity, improve data quality, and enhance decision-making.

Relocation Options:

Relocation could be considered.

International Considerations:

Expatriate assignments will not be considered.

Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position

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