Summary
What you’ll impact
The Principal GenAI Engineer will lead the design, development, and deployment of large language model solutions, ensuring scalable, high-performance code and cloud integration. This role involves cross-functional collaboration, mentorship of engineering teams, and driving best practices in GenAI and LLM technologies.
Responsibilities
What you'll do
- 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.
Requirements
What you’ll bring
- 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
- Experience: 8+ years only