Experience Level: Principal (8-14 years)
About the Role
Client is hiring a Principal GenAI Engineer with strong expertise in LLMs to lead enterprise-scale AI implementations for Fortune 500 clients. This role focuses on building RAG systems that combine structured semantic reasoning with advanced LLM architectures to deliver scalable, explainable, production-grade AI solutions.
What We’re Looking For
- 8-13 years of experience in ML/AI systems
- 2+ years hands-on experience with LLMs (RAG, agents, prompt engineering)
- Strong proficiency in Python, LangGraph, and SQL
- Experience deploying GenAI systems on AWS / Azure / GCP
- Develop and optimize LLM-based solutions : Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
- Codebase ownership : Build and maintain/review high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
- Cloud integration : Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
- Cross-functional collaboration : Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
- Mentoring and guidance : Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.