Description

Design and implement end-to-end Generative AI architectures using LLMs and AI platforms. Define solution patterns for prompt engineering, RAG, and fine-tuning. Collaborate with business, data, and engineering teams to identify and validate GenAI use cases. Select and integrate GenAI tools, frameworks, and APIs while ensuring security, privacy, and compliance standards. Guide development teams on best practices and monitor performance, cost, and scalability. Document architecture designs and technical guidelines.

Responsibilities

• Design end-to-end Generative AI architectures using LLMs and AI platforms.
• Define solution patterns for prompt engineering, RAG, and fine-tuning.
• Collaborate with business, data, and engineering teams to identify GenAI use cases.
• Select and integrate GenAI tools, frameworks, and APIs.
• Ensure AI solutions meet security, privacy, and compliance standards.

Required Skills

• 7+ years of experience in Generative AI and Large Language Models (LLMs).
• Strong understanding of prompt engineering, embeddings, and RAG architectures.
• Proficiency in Python and AI/ML frameworks.
• Experience integrating AI models via APIs.
• Knowledge of cloud platforms (AWS, Azure, GCP).
• Understanding of data pipelines and vector databases.
• Strong problem-solving and communication skills.

Preferred Skills

• Experience guiding development teams on GenAI best practices and architecture standards.
• Ability to monitor and optimize performance, cost, and scalability of GenAI solutions.

Key Skills

Education

Any Graduate