LLM Specialist

Role Summary
The Large Language Model (LLM) Specialist is responsible for leading the design, development, and deployment of advanced generative AI capabilities within a cloud-based analytics environment. This senior-level role involves driving innovation in LLM architecture, strategy, and implementation while ensuring scalable, secure, and high-performance solutions. Collaborating across engineering, product, and data teams, the specialist provides technical leadership and evaluates emerging LLM technologies to facilitate practical AI transformation initiatives.

Responsibilities

• Lead the architecture, development, and operationalization of large language models and generative AI solutions.
• Design and implement end-to-end retrieval-augmented generation (RAG) pipelines, including embedding workflows, retrieval optimization, and vector database integration.
• Drive innovation around advanced LLM techniques such as finetuning, parameter-efficient training, and prompt engineering.
• Oversee the development of high-impact prototypes and scalable LLM pipelines for enterprise deployment.
• Evaluate and recommend emerging AI/ML tools, frameworks, and architectures to enhance model performance and reliability.
• Ensure models and workflows adhere to governance, security, and performance standards within cloud platforms like Azure, AWS, or GCP.
• Provide technical guidance and mentorship to team members and facilitate effective communication of complex AI concepts.
• Establish best practices for MLOps/LLMOps, including version control, CI/CD, automated testing, monitoring, and governance frameworks.
• Collaborate across teams to integrate LLM solutions into large-scale analytics environments such as Databricks, Snowflake, or Spark.
• Stay current with advances in AI/ML research, evaluating their applicability and potential impact on organizational objectives.

Qualifications

• Bachelor’s degree in computer science, software engineering, or a related field.
• 5-7 years of experience in AI, machine learning, or related roles, with demonstrated expertise in LLM architectures and generative AI techniques.
• Deep knowledge of transformer models, fine-tuning, prompt engineering, and advanced retrieval methods.
• Hands-on experience with LLM frameworks (e.g., LangChain, LlamaIndex) and orchestration tools.
• Strong Python programming skills and experience working in distributed or GPU-accelerated environments.
• Proven ability to develop and deploy AI/ML workflows within cloud platforms such as Azure, AWS, or GCP.
• Solid understanding of MLOps/LLMOps practices, including versioning, CI/CD, automated testing, and model governance.
• Ability to lead technical discussions, mentor teams, and communicate complex concepts effectively.
• This position requires eligibility for a U.S. Government security clearance. In accordance with federal law, U.S. citizenship is required.

Publishing Pay Range: $45.00 – $55.00 USD Hourly

This is a fully remote role and can be performed from an approved location.