AI Engineer / LLM Developer (Microsoft Foundry)

Role overview

Responsibilities

• check_circle Design, develop, and deploy production-grade AI applications using the Microsoft Foundry platform.
• check_circle Build custom Generative AI solutions leveraging Large Language Models (LLMs) to solve complex business problems.
• check_circle Develop AI-powered applications that integrate seamlessly with the Microsoft ecosystem, including Azure services, Microsoft Fabric, and Power Platform where appropriate.
• check_circle Build and optimize Retrieval-Augmented Generation (RAG) solutions and other enterprise AI architectures.
• check_circle Develop Python-based services, APIs, and automation workflows supporting AI applications.
• check_circle Evaluate, fine-tune, and optimize LLM performance for accuracy, scalability, and business value.
• check_circle Collaborate with business stakeholders to translate business problems into AI-driven solutions.
• check_circle Integrate enterprise data sources into AI applications while ensuring security and governance best practices.
• check_circle Prototype new AI capabilities and transition successful prototypes into production.
• check_circle Document AI architectures, development standards, and implementation best practices.
• check_circle Stay current with emerging AI technologies and recommend practical applications for the organization.

Basic qualifications

• 4+ years of professional software development experience with advanced Python.
• Hands-on experience building and deploying applications on the Microsoft Foundry platform.
• Demonstrated experience developing production LLM-based applications—not just experimentation or theoretical knowledge.
• Experience with prompt engineering, model evaluation, and LLM optimization techniques.
• Experience integrating AI solutions with enterprise data sources and APIs.
• Strong understanding of AI application architecture and scalable solution design.
• Experience building REST APIs and Python-based backend services.
• Experience working with large and complex datasets.
• Strong communication skills with the ability to explain AI concepts to technical and business audiences.
• Experience within financial services is highly desirable.

Preferred qualifications

• Microsoft Fabric experience.
• Azure AI Services / Azure OpenAI.
• Vector databases and Retrieval-Augmented Generation (RAG).
• Semantic search and embeddings.
• Power BI integration.
• Machine Learning experience.
• MLOps or AI deployment pipelines.
• Experience with LangChain, Semantic Kernel, AutoGen, or similar AI frameworks.