AI Quality & Reliability Engineer (QA/SRE)

About the role

We are seeking an AI Quality & Reliability Engineer to own the production readiness of our cloud‑based AI solutions. This hybrid role blends automated software testing, AI model evaluation, and Site Reliability Engineering to ensure resilient, performant, and banking‑compliant services on Azure and AWS.

Key responsibilities

• Design and execute automated testing frameworks for AI services, covering model hallucinations, accuracy, content safety, and latency.
• Implement chaos engineering and load testing to guarantee web/mobile back‑ends can handle banking‑scale traffic and maintain high availability.
• Build CI/CD‑integrated regression suites in Python that validate application logic and infrastructure state (IaC validation).
• Define and monitor Service Level Indicators (SLIs) and Objectives (SLOs), setting up advanced alerting in Azure Monitor or AWS CloudWatch.
• Automate security scans and compliance checks to meet strict banking data residency and privacy protocols.

Required profile

• Strong automation stack experience with Python and frameworks such as PyTest, Selenium, or Robot Framework.
• Hands‑on expertise with Azure or AWS, especially networking, scaling, and serverless reliability.
• Understanding of prompt engineering and AI output evaluation methods (RAG, ROUGE/BLEU, custom LLM benchmarks).
• Proficiency with monitoring tools like Grafana, Prometheus, or native cloud monitoring services.
• FinOps awareness to identify costly failing tests and inefficient cloud resource usage.

Required skills

• Python
• Bash scripting
• GitHub Actions
• Terraform
• K6
• JMeter
• DeepEval
• Ragas
• LangSmith
• Azure
• AWS
• Prometheus
• Grafana
• Selenium
• Robot Framework
• PyTest