Platform Site Reliability Engineer

Dicetek LLC; Abu Dhabi; Hybrid; AED 120,000 - 180,000; Full time

Job summary

Dicetek LLC is looking for a Site Reliability Engineer (SRE) in Abu Dhabi to improve the production readiness of our cloud-based AI systems. In this hybrid role, you will focus on resiliency engineering through automated testing and ensuring the reliability of our Azure and AWS infrastructure.

The ideal candidate will have strong Python skills and experience in AI testing, cloud infrastructure, and CI/CD processes. Responsibilities include implementing chaos engineering, building automated regression tests, and monitoring key performance indicators.

Qualifications

• High proficiency in Python, particularly for AI testing.
• Strong hands-on experience with Azure or AWS.
• Experience with CI/CD integrated test suites.

Responsibilities

• Implement 'Chaos Engineering' and load testing.
• Build CI/CD-integrated test suites using Python.
• Define and monitor Service Level Indicators (SLIs).
• Automate security scans and compliance checks.

Skills

Python

Proficiency in CI/CD frameworks

Understanding of AI/ML

Experience with cloud infrastructure

Tools

PyTest

Selenium

Grafana

Terraform

Job description

Site Reliability Engineer (SRE)

Role Overview

We are seeking an SiteReliability 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.

Key Responsibilities

• 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 CloudWatch 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.

Technical & Professional Requirements

• 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.
• FinOps Awareness: Ability to identify expensive failing tests or inefficient cloud resource usage during the testing phase.

Recommended Skillset & Tools

• Languages: Python (Mandatory), Bash scripting.
• Tools: GitHub Actions (CI/CD), Terraform (reading/validating), K6 or JMeter (Performance).
• AI Frameworks: DeepEval, Ragas, or LangSmith (for automated AI evaluation).