Senior LLM Engineer

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Requirements:

• Proven experience with Cloud Platforms (AWS, GCP or Azure)
• Hands-on experience working with Vector databases such as PineCone,Chroma, MongoDB and LanceDB.
• Solid understanding of LLM concepts, such as prompt engineering, model fine-tuning, and transfer learning.
• Familiarity with one popular LLM frameworks (e.g., OpenAI GPT, Hugging Face Transformers).
• Minimum 5 years of experience in Python programming, with a strong focus on developing LLM applications.
• Proven experience with automation and scaling.
• Experience building and/or integrating Voice AI solutions is a big plus.
• Strong problem-solving skills and the ability to work independently.
• Excellent communication skills, with the ability to present complex concepts to both technical and non-technical audiences.
• Experience working in a cross-functional team and collaborating with stakeholders at various levels of the organization.
• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Experience with DevOps toolsets such as Terraform, Prometheus, etc. and Understanding of Docker,Kubernetes and CI/CD tools such as Gitlab CI,ArgoCD and Helm charts gets you bonus points
• Experience with web frameworks such as FastAPI, Django, Streamlit for building production ready applications gets you bonus points.

Responsibilities:

• Design and implement a high-performance, scalable and reliable LLM service using Python, LLM Services (E.g., OpenAI, Antropic’s Claude,Meta’s LLaMA etc) and AWS technologies to power our applications and business needs including building services that can serve hundreds of concurrent users in a second.
• Design and development of RAG pipelines
• Building or integrating Voice related AI technologies and productizing at scale
• Collaborate with business leaders to understand their needs and challenges, and identify potential LLM use cases.
• Design, develop, and deploy custom LLM solutions tailored to the requirements of different divisions, including co-creating the prompts.
• Collaborate with the Data Science team to understand how to build the LLM solution including fine tuning OpenAI models as necessary.
• Implement software best practices to ensure seamless development, testing, and deployment of LLM solutions.
• Stay up-to-date with the latest advancements in LLM technologies, and continuously explore ways to integrate these advancements into our 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 technical support and training to internal teams as needed.
• Monitor LLM performance and make improvements to ensure acceptable response times based on use cases.
• Collaborate with other developers and data scientists within the organization to share knowledge, ideas, and best practices.
• Participate in code reviews and provide guidance to junior developers.