As an Azure AI Foundry you will be involved in building, fine-tuning, and deploying AI/ML models, designing AI pipelines, and integrating them with enterprise applications using Azure services like Azure Machine Learning, Azure DevOps, and Cognitive Services. Key responsibilities include working with large language models (LLMs) and prompt engineering, collaborating with stakeholders, and applying best practices for AI development and deployment. The ideal candidate will have strong programming skills, experience with Azure DevOps, and a background in AI/ML development. Ideal applicant should have expertise in:
AI Services Integration – particularly with Azure Cognitive Services (vision, language, speech) and Azure Machine Learning
End-to-End AI Lifecycle Management – including data ingestion, preprocessing, model training, evaluation, and deployment
Key responsibilities:
Model Development: Build, fine-tune, and deploy AI models using the Azure AI Foundry platform, which includes a catalog of frontier and open-source models from partners like OpenAI and Hugging Face.
Pipeline and Integration: Design and optimize AI pipelines for scalability, performance, and cost-effectiveness. Integrate AI models and agents with enterprise applications.
Prompt Engineering: Implement prompt engineering and other techniques for effective model interaction and performance.
Stakeholder Collaboration: Work with business stakeholders to understand requirements and translate AI concepts into deployable solutions.
DevOps and CI/CD: Apply best practices in AI development, testing, and deployment using tools like Azure DevOps and Git for CI/CD pipelines.
Responsible AI: Implement and adhere to responsible AI practices throughout the development lifecycle.
Required qualifications and skills:
Minimum Experience: 6-8 years of experience in AI/ML development with hands-on experience using Azure AI Foundry and related services.
Programming: Strong programming skills in languages such as Python, C#, or equivalent.
LLMs: Experience with large language models, prompt design, and AI integration.
Azure: Familiarity with Azure services, particularly Azure DevOps, Azure Machine Learning, and Cognitive Services.
Collaboration: Ability to work collaboratively in an agile environment and strong problem-solving skills.
