Mekari is Indonesia's no. 1 Software-as-a-Service (SaaS) company. With our ecosystem of software solutions—including Mekari Jurnal, Mekari Talenta, Mekari Qontak, and Mekari Flex, we aim to facilitate entrepreneurs and leaders as they accelerate the digital transformation of their businesses.

In our 10+ years of journey we have reached over 1 Million platform users, and we're not planning to stop any time soon. We need more people like you: builders and owners with calculated ambition who are eager to grow and create their #BiggestImpact.

The Mission
We are looking for a visionary Senior QA Engineer II - SDET to lead the convergence of Quality Engineering and Artificial Intelligence. You will be responsible for building the next generation of our "Self-Healing" automation infrastructure and establishing the guardrails for testing our proprietary AI/ML features. You are a developer first, with a passion for quality and a deep understanding of the modern AI stack.

Key Responsibilities :

• AI-Driven Infrastructure: Design and build internal tools that leverage LLMs or Machine Learning to auto-generate test cases, identify flaky tests, and perform root-cause analysis on logs.
• Testing "The Black Box": Develop frameworks to validate AI model outputs, ensuring accuracy, identifying hallucinations, and monitoring for data drift in production.
• Architecture & Strategy: Set the technical standards for automation across all squads. Ensure our framework is modular, scalable, and capable of running thousands of tests in parallel.
• Shift-Right Quality: Implement AI-powered observability and synthetic monitoring to catch regressions in production before users do.
  Mentorship: Act as the highest technical authority for the QA guild, upskilling Senior SDETs in AI/ML testing patterns.

Technical Requirements :

• Core Engineering: 8+ years of experience in Software Engineering or SDET roles, with mastery of Typescript/Python (preferred for AI) or Java/Go.
• AI/ML Proficiency: * Experience with LLM integration (OpenAI API, LangChain, or LlamaIndex) for automation.
• Understanding of model evaluation metrics (e.g., ROUGE, BLEU, or custom scoring via GPT-4-as-a-judge).
• Familiarity with vector databases (Pinecone, Milvus) and prompt engineering.
• Advanced Automation: Expert-level experience with Playwright or Cypress and building custom libraries on top of them.
• Infrastructure as Code (IaC): Proficiency with Terraform, Docker, and Kubernetes to manage isolated test environments.
• Data Science Lite: Ability to use SQL and data visualization tools to analyze large sets of test results for predictive trends.

The "AI Specialist" Requirements :

• Model Observability: Experience with tools like Weights & Biases or Arize to monitor model performance.
• Prompt Regression: Experience building "Golden Datasets" to ensure new model deployments don't degrade existing prompt responses.
• Security & Bias: Knowledge of AI security (Prompt Injection testing) and bias detection in automated decision-making.