LLM Engineer

LLM Engineer
12 month contract
100% Remote

Position Summary

Position Summary
The LLM Engineer is responsible for designing, developing, and deploying large language model solutions that support enterprise operations. This role focuses on Azure AI services, Azure OpenAI, and the integration of LLM capabilities into internal applications and workflows. The engineer will work closely with cross-functional teams to turn business requirements into scalable, production-ready AI solutions.

Key Responsibilities
• Design, develop, and deploy LLM-based applications using Azure AI, Azure OpenAI, and related cloud services
• Build retrieval-augmented generation (RAG) pipelines, embeddings, vector stores, and prompt workflows
• Integrate LLM capabilities into enterprise platforms such as Power Platform, Microsoft 365, and internal systems
• Prepare, clean, and transform data for LLM consumption and build feature and inference pipelines
• Implement model monitoring, lifecycle management, evaluations, and performance tuning
• Collaborate with automation engineers, product owners, and business stakeholders to assess and scope use cases
• Document solution architectures, model workflows, and technical designs
• Evaluate emerging AI tools, frameworks, and best practices
• Support troubleshooting, testing, and responsible AI standards

Required Skills and Experience
• Strong hands-on experience with Azure AI services, Azure OpenAI, or similar LLM platforms
• Proficiency in Python and common ML libraries (scikit-learn, pandas, PyTorch, TensorFlow)
• Practical experience building and deploying LLM applications, including embeddings, RAG, prompt engineering, and fine-tuning
• Understanding of data pipelines, model evaluation, and monitoring
• Experience integrating LLM solutions into enterprise systems
• Ability to communicate complex AI concepts clearly to both business and technical stakeholders

Preferred Experience
• Exposure to Power Platform AI Builder, Copilot Studio, or Microsoft 365 Copilot integrations
• Familiarity with MLOps tools and practices
• Experience with vector database technologies such as Pinecone, Redis, or Azure AI Search

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