AI Engineer Position Available In Fulton, Georgia
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Job Description
AI Engineer Georgia, Atlanta 06/16/2025 Contract Active
Job Description:
Job Summary
We are seeking a self-driven AI Engineer with expertise in generative AI development on Microsoft platforms. This role involves designing, developing, and deploying scalable AI solutions using tools such as Microsoft Copilot, Azure OpenAI, and Power Automate.
The ideal candidate will have strong full-stack and DevOps skills, experience with LLMs and agentic frameworks, and a passion for building healthcare-compliant AI systems. Key Responsibilities
Design and implement generative AI applications using LLMs (e.g., GPT, Copilot) and agentic frameworks.
Build rapid prototypes and production-ready agents using Microsoft Copilot, Power Automate, MS Flow, and Azure services.
Integrate and evaluate third-party AI platforms (e.g., OpenAI, Anthropic, Cohere).
Develop LLM evaluation frameworks using tools like RAGAS and human-in-the-loop validation.
Solve complex challenges related to scalability, performance, and compliance in AI systems.
Build and maintain internal tools and UIs using React, REST/GraphQL.
Deploy AI systems in cloud environments with a focus on healthcare compliance (e.g., HIPAA). Required Qualifications
3+ years of hands-on experience in AI/ML development, with at least 1 year focused on generative AI on Microsoft platforms.
Proficiency in Python and JavaScript/TypeScript.
Experience with Microsoft Copilot, Azure OpenAI, Azure ML, Cognitive Search, and Health Data Services.
Familiarity with vector databases (e.g., Pinecone, FAISS, OpenSearch).
Experience with full-stack development (React, REST/GraphQL).
Strong DevOps skills including CI/CD pipelines, Git, and observability tools (e.g., CloudWatch, Grafana).
Ability to work independently and drive projects from concept to deployment. Preferred Qualifications
Familiarity with HIPAA or other regulated data environments.
Exposure to traditional ML tools (e.g., scikit-learn, pandas).
Experience with security best practices in the software development lifecycle.
