AI System Test Engineer

18 hours ago

Bengaluru, Karnataka, India MeshDefend Full time ₹ 12,00,000 - ₹ 36,00,000 per year

MeshDefend
is an early-stage VC funded startup that is building AI-Native Agentic Operating System for

Enterprise Data Infrastructure. We are creating AI Agents to make Data Infrastructure Intelligent,

Autonomous and Secure. Our founding team is composed of seasoned technologists and inventors, each

with a track record of building global product portfolios valued in the billions. Here, you won't just follow a blueprint; you'll take the wheel and help set the course, leveraging cutting-edge solutions to redefine what's possible. If you're driven by innovation and crave hands-on influence over both product direction and technical architecture, this is the place to make your mark.

We are seeking an AI System Test Engineer who is passionate about quality and thorough system testing.

We are looking for an engineer who deeply empathizes with customers, is an expert in automation, and

possesses strong technical fundamentals. In this role, you will design and execute comprehensive system

test plans for AI agent-based solutions, including autonomous agents and multi-agent systems. You will

write automated test scripts to check product accuracy and responsiveness, collaborating with UX, AI, and

Backend Architects.

Day-to-day, you will actively gather customer feedback to inform test case development, ensuring

customer scenarios are incorporated into all aspects of testing. You will advocate for customer-centric

improvements throughout the product lifecycle, collaborating with founders to establish a customer-first

mindset and best practices. Your technical expertise and automation skills will be key to delivering high

quality, impactful solutions that address real-world needs and drive the evolution of our AI-native platform.

We are looking for AI System Test Engineer who has 3-5 years of hands-on experience:


• Programming Languages: Python, Go, Shell Script


• AI: GenAI, LLMs, Prompt Engineering, RAG, Machine Learning (ML)


• CI/CD: Jenkins, GitHub actions, GitHub runners and self-hosted runners


• Test Frameworks and Reporting: Pytest, Selenium, Allure


• Containers: Docker Images, Docker Engine, Kubernetes, Helm


• Observability: Grafana, Prometheus, ELK/EFK Stack, Splunk, Nagios


• Database: Relational Database (PostgreSQL, MS SQL), Search (ElasticSearch/OpenSearch), Vector DBs


• Infrastructure: Linux (OS Management), Networking (Protocols), Storage, Memory, Security

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