Emids is a leading provider of digital transformation solutions to the healthcare industry, serving payers, providers, life sciences, and technology firms. Headquartered in Nashville, Emids helps bridge critical gaps in providing accessible, affordable, and high-quality healthcare by providing digital transformation services, custom application development, data engineering, business intelligence solutions, and specialized consulting services to all parts of the healthcare ecosystem. With nearly 3,500 professionals globally, Emids leverages strong domain expertise in healthcare-specific platforms, regulations, and standards to provide tailored, cutting-edge solutions and services to its clients.

We work at the intersection of design, engineering, and domain expertise, our passionate team of problem solvers work closely with customers to blaze new trails that will positively impact the future of health. We are a truly global company, we rely on diversity and together we create a workplace that brings the best out of everyone. Using technology and insights, we move nimbly and provide trusted advice, seeking ways to amplify results.

We’re committed to bettering healthcare and empowering wellness.

We are seeking a highly skilled Senior AI Engineer to lead the development and enhancement of AI-driven workflow for document classification and complaint coding, focussed on the development, testing, and fine-tuning of the model to ensure high accuracy, low operating cost, and high throughput. The ideal candidate will have deep expertise in Azure AI Foundry, LLM selection and tuning, RAG techniques, and vector databases, along with proficiency in Python or Node.js. This role is crucial in automatic workflows to rapidly classify documents into categories, identify key individuals within the document, and store this information in a structured data format, ensuring accuracy and efficiency in AI-powered insights.

Key Responsibilities:

• Implement LLM-based AI agents and optimize their performance using advanced prompt engineering and retrieval-augmented generation (RAG) techniques.
• Deploy your model(s) in an Azure production workflow and implement a learning mechanism to ensure that human feedback on the results helps to continually improve the accuracy of the model over time.
• Vectorize structured and unstructured data to enhance search accuracy and AI-driven insights.
• Work with vector databases (ChromaDB, Pinecone, Weaviate, Azure Search) and integrate them with AI models.
• Manage SQL (PostgreSQL, MySQL) and NoSQL databases (MongoDB, Elasticsearch) for efficient data processing.
• Build and integrate RESTful APIs (FastAPI, Flask, ExpressJS) to expose AI functionalities.
• Stay updated on advancements in LLMs, embedding models, and AI frameworks, applying the latest techniques to improve system capabilities.
• Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to deliver high-impact AI solutions.

Qualifications & Skills:

• Proficiency in Python or Node.js, with hands-on experience in AI agent development.
• Strong experience in Azure AI Foundry and associated AI tools.
• Expertise in LLM APIs, prompt engineering, and fine-tuning models using RAG.
• In-depth understanding of vectorization techniques for AI performance enhancement.
• Experience working with vector databases (ChromaDB, Pinecone, Weaviate, Azure Search).
• Familiarity with SQL and NoSQL databases for structured and unstructured data processing.
• Ability to develop and integrate RESTful APIs using FastAPI, Flask, or ExpressJS.
• Strong problem-solving skills with a focus on AI-driven automation and optimization.

Preferred Qualifications:

• Experience in deploying AI models in Azure.
• Knowledge of MLOps best practices for managing AI model lifecycle.
• Exposure to NLP, knowledge graphs, and semantic search.