LLM Engineer

• Design and implement a high-performance, scalable and reliable LLM service using Python, LLM Services (including OpenAI, Antropic’s Claude, and Meta’s LLaMA) and Cloud technologies to power applications and business needs including building services that can serve hundreds of concurrent users in a second.
• Design and develop RAG pipelines Building Search Engines and Recommendation engines on domain speciﬁc corpus.
• Collaborate with business leaders to understand their needs and challenges, and identify potential LLM use cases.
• Monitor LLM performance and make improvements to ensure acceptable response times based on use cases.
• Participate in code reviews and provide guidance to junior developers.
• Mentor LLM and AI Engineers to help deliver the AI use cases across the company. Perform LLM modeling, fine tuning and deployment of advanced AI technology solutions.
• Collaborate with cross functional teams to understand how to build LLM software solutions, including fine-tuning LLM models.
• Utilize strong communication skills (written and verbal) to convey technical concepts and collaborate technical concepts and collaborating with cross-functional teams.
• Collaborate with other developers and data scientists within the organization to share knowledge, ideas, and best practices.
• Design, develop and deploy Large Language Models (LLM) software solutions to facilitate AI needs for all enterprise and business use cases.
• Implement software best practices to ensure seamless development, testing, and deployment of LLM software solutions.
• Collaborate with business leaders to understand their needs and challenges, and identify potential LLM use cases that provide best ROI opportunities.
• Stay up-to-date with the latest advancements in LLM technologies, and continuously explore ways to integrate these advancements into existing solutions.
• Develop and maintain comprehensive documentation, including technical specifications, user guides, and best practices.
• Ensure data privacy and security compliance while working with LLMs.
• Provide support and training to internal teams as needed.

Principal Large Language Model Engineer

ML Ops Engineer – Data Lake, AI Infrastructure

Director – AI Infrastructure

Generative AI Engineer – Enterprise Value Creation

AI Infrastructure Business Development Manager – Verticals

AI Infrastructure Deployment Lead