Description

You will lead quality engineering for AI and machine learning systems, focusing on GenAI applications and RAG pipelines.

This role is on-site.

Responsibilities

• Design and implement automated testing frameworks for AI/ML models and LLM-based applications.
• Build and maintain RAG pipelines using LangChain, LlamaIndex, and LangGraph.
• Develop backend services using Python, FastAPI, or Flask, ensuring reliability and performance.
• Integrate and test vector databases (e.g., Neo4j) and cloud AI services like Amazon Bedrock.
• Manage CI/CD pipelines for model deployment and infrastructure using Docker and Kubernetes.

Required Skills

• 8+ years of experience in software engineering or quality assurance.
• Strong proficiency in Python and frameworks like FastAPI or Flask.
• Hands-on experience with AI/ML, GenAI, TensorFlow, PyTorch, and Scikit-learn.
• Practical knowledge of LangChain, LlamaIndex, and LangGraph for building AI applications.
• Experience with AWS, Docker, Kubernetes, and CI/CD practices.
• Familiarity with vector databases and RAG architecture.

Preferred Skills

• Experience with Playwright or Selenium for end-to-end testing.
• Knowledge of Neo4j graph database integration.

Key Skills

Education

Any Graduate