Generative AI Architect

Project description

Development of enterprise-grade Generative AI solutions built on LLMs. The project focuses on scalable architectures, RAG-based systems, and agent-driven workflows integrated with cloud and backend platforms.

Responsibilities

• Design and evolve end-to-end GenAI architectures.

• Select and apply LLMs, prompting, and fine-tuning strategies.

• Build and maintain RAG pipelines and vector-based retrieval.

• Design agentic workflows and orchestration.

• Integrate GenAI components with backend and cloud infrastructure.

• Ensure observability, security, and production readiness.

Requirements

• Hands-on experience with LLMs and GenAI system design.

• Understanding of RAG, vector databases, and agentic AI.

• Strong Python and backend integration experience.

• Cloud architecture and scaling knowledge.

• Proven architectural experience in complex systems.