Description

You will design and deploy scalable generative AI solutions, integrating LLMs and RAG into enterprise systems.

Responsibilities

• Build modular AI components and reusable templates for seamless integration with existing infrastructure.
• Implement and maintain CI/CD pipelines, ensuring reliability, scalability, and observability of GenAI applications.
• Collaborate with architects to adhere to reference architectures and standards in AI development.
• Optimize prompts, troubleshoot deployed applications, and tune performance for stability.
• Produce clear technical documentation and share knowledge to improve team capabilities.

Required Skills

• 5+ years of experience building and deploying GenAI applications using LLM APIs and frameworks.
• Hands-on expertise with Retrieval-Augmented Generation (RAG) and vector databases.
• Proficiency with cloud platforms (AWS, Azure, or GCP) and containerized environments (Docker, Kubernetes).
• Strong understanding of CI/CD pipelines, modern deployment practices, and release management.
• Experience with agent-based systems, tool integrations, and model evaluation.
• Proven track record of contributing to shared engineering standards or frameworks.
• Bachelor's degree in a relevant field or equivalent practical experience.

Preferred Skills

• Familiarity with advanced prompt engineering techniques and performance optimization strategies.
• Experience integrating GenAI into large-scale enterprise systems with complex architectural requirements.

Key Skills

Education

Any Gradute