About Deccan AI
Deccan AI is a high-growth, venture-backed AI model training and evaluation company headquartered in the Bay Area. Founded by alumni of IIT Bombay, IIM Ahmedabad, and ex-Google, we partner with the world’s top AI frontier labs including Google DeepMind, Snowflake, and several cutting-edge research groups. We are backed by Prosus Ventures, and our India office is based in Hyderabad.
We’re not just participating in the AI race we’re building the infrastructure that powers it.
With 1M+ global experts, advanced automation, and vertically integrated platforms, we deliver the gold-standard data that world-class AI models rely on. The AI data annotation market is exploding set to quadruple by 2032. The opportunity? Massive, and you can help define the future.
Key Requirements:
• 1–3 years of solid hands-on automation engineering experience
• Experience contributing to or building UI automation frameworks
• Experience with UI automation tools such as:
Selenium, Playwright, Cypress, TestNG, Cucumber, PyTest, etc.
• Experience with API automation tools such as:
RestAssured, PyTest, Postman, Karate, etc.
• Basic exposure to Mobile automation (Appium or WebdriverIO)
• Basic performance testing exposure using:
JMeter, k6, etc.
• Strong programming fundamentals in Java / Python / JavaScript
• Understanding of CI/CD integration concepts
• Experience working with Bitbucket and GitHub repositories
• Basic understanding of microservices and distributed systems
• Exposure to cloud environments (AWS / GCP / Azure preferred)
• Strong debugging and analytical skills
AI / ML Testing Exposure (Preferred):
• Understanding of LLM output validation
• Exposure to prompt testing and regression validation
• Basic understanding of hallucination detection and grounding validation
• Familiarity with AI evaluation concepts such as semantic similarity scoring and response consistency
• Interest in building structured AI validation pipelines
Responsibilities:
• Develop and maintain UI and API automation suites
• Execute functional, regression, and performance test cycles
• Contribute to automation integration in CI/CD pipelines
• Support validation of AI-driven features and outputs
• Improve test stability, coverage, and execution efficiency
• Collaborate with senior engineers to enhance framework architecture
• Ensure quality standards across multi-cloud deployments