AI Engineer (Only local to NC and w2 Candidate )

Dice is the leading career destination for tech experts at every stage of their careers. Our client, EdgeAll, is seeking the following. Apply via Dice today!

We are seeing a highly skilled senior AI Engineer to join our innovative team. The ideal candidate will be responsible for developing and deploying intelligent AI solutions using VS Code, Azure AI Studio, and Databricks. You will integrate AI powered solutions across multiple channels like Web applications, etc.

Key Responsibilities

• Design, develop and deploy intelligent conversational AI solutions using Azure AI technologies, and Databricks.
• Utilize VS code, Databricks and AI studio for model development, testing, deployment, and monitoring.
• Build and manage AI agents for automation and advanced conversational experiences.
• Integrate the AI services into applications using python frameworks such as Django, FastAPI, and Flask; build secure REST endpoints, async workers, and SDK-based clients.
• Collaborate with cross functional teams to gather requirements, design conversational flows, and implement scalable solutions.
• Monitor and optimize AI model performance, ensuring reliability and accuracy.
• Develop reusable components and pipelines in Azure AI and Databricks for rapid solution deployment.
• Ensure adherence to data privacy and security standards within all AI implementations.

Technical skills and qualifications

• BS or MS in Computer Science, Engineering, or related fields
• Proven experience working with Azure AI services (e.g. Azure OpenAI, Azure Bot service, Cognitive services, Copilot)
• Hands-on experience with Databricks Genie and building AI agents for enterprise use cases.
• Familiarity with MCP for secure and standardized integration of AI models with external tools and APIs.
• Strong understanding of NLPs, LLMs and RESTful API integration.
• Familiarity with Microsoft Copilot, Github Copilot, Azure AI Services, Databricks including practical experience with Azure Machine Learning and Azure Open AI
• Proven experience with AI/ML model evaluation, deep understanding of machine learning algorithms and data processing techniques
• Expertise in designing MLOps pipelines, encompassing model registry security, secure model deployment, and runtime security monitoring for AI models.