Platform Site Reliability Engineer

Site Reliability Engineer (SRE) Role Overview

We are seeking an Site Reliability Engineer to own the "Production Readiness" of our cloud-based AI solutions. This hybrid role combines automated software testing and Site Reliability Engineering (SRE). You will build the automated frameworks that validate our AI outputs and ensure the underlying Azure/AWS infrastructure is resilient, performant, and compliant with banking standards.

• Resiliency Engineering (SRE):
  Implement "Chaos Engineering" and load testing to ensure web/mobile backends can handle banking-scale traffic. Maintain high availability through automated recovery scripts.
• Automated Regression:
  Build CI/CD‑integrated test suites using Python that validate both the application logic and the infrastructure state (IaC validation).
• Observability & SLIs:
  Define and monitor Service Level Indicators (SLIs) and Objectives (SLOs). Set up advanced alerting in Azure Monitor or AWS Cloud Watch to catch performance degradation before users do.
• Security & Compliance Testing:
  Automate security scans and compliance checks to ensure all AI data handling meets strict banking data residency and privacy protocols.

• Automation Stack:
  High proficiency in Python (for AI testing) and framework automation (PyTest, Selenium, or Robot Framework).
• Cloud Infrastructure:
  Strong hands‑on experience with Azure or AWS, specifically regarding networking, scaling, and serverless reliability.
• AI/ML Understanding:
  Understanding of Prompt Engineering and how to evaluate AI model outputs (RAG evaluation, ROUGE/BLEU scores, or custom LLM‑benchmarks).
• Monitoring Tools:
  Experience with Grafana, Prometheus, or native cloud monitoring tools to build real‑time reliability dashboards.
• Fin Ops Awareness:
  Ability to identify expensive failing tests or inefficient cloud resource usage during the testing phase.

• Languages:
  
  Python (Mandatory), Bash scripting.
• Tools:
  Git Hub Actions (CI/CD), Terraform (reading/validating), K6 or JMeter (Performance).
• AI Frameworks:
  Deep Eval, Ragas, or Lang Smith (for automated AI evaluation).