Description

You will build and maintain GenAI applications using Python, focusing on RAG pipelines and prompt engineering.

This role is hybrid.

Responsibilities

• Develop and manage GenAI lifecycle components, including RAG pipelines and AI safety mechanisms.
• Build scalable APIs and services using FastAPI, integrating with MongoDB and Redis.
• Deploy and containerize Python applications using Docker and Kubernetes (OpenShift).
• Implement and configure Kafka queue integrations for asynchronous processing.
• Apply model testing and evaluation frameworks to ensure performance and reliability.

Required Skills

• 5+ years of professional experience with object-oriented Python development.
• Deep expertise in GenAI lifecycle management and Retrieval-Augmented Generation (RAG) architectures.
• Proficiency in prompt engineering and AI safety techniques.
• Hands-on experience with MongoDB, Redis, and FastAPI.
• Strong knowledge of containerization using Docker and Kubernetes.
• Experience with Kafka queue integration and configuration.
• Understanding of DevOps practices and enterprise tooling.
• Ability to work effectively in regulated environments with cross-functional teams.

Preferred Skills

• Experience with model testing and evaluation frameworks for AI reliability.
• Background in deploying applications on OpenShift.

Key Skills

Education

Any Graduate