Design, develop, and integrate GenAI-powered applications using large language models and related AI services
Build solutions involving prompt engineering, retrieval-augmented generation, embeddings, vector search, and AI agents
Develop APIs, services, and application components that connect GenAI capabilities to business workflows
Work with structured and unstructured data to support knowledge retrieval, summarization, classification, and content generation use cases
Evaluate model performance, response quality, hallucination risk, and reliability across different scenarios
Collaborate with product, data, engineering, and architecture teams to deliver scalable AI solutions
Implement responsible AI practices including security, privacy, monitoring, explainability, and governance considerations
Support deployment and release processes using tools such as Azure DevOps, Git, CI/CD pipelines, and cloud environments
Create documentation, reusable patterns, and technical guidance for GenAI solution development
Stay current with emerging GenAI frameworks, model capabilities, and best practices Required Qualifications
3+ years of software engineering, data engineering, machine learning, or AI application development experience
Hands-on experience building applications with large language models
Experience with prompt engineering, RAG architectures, embeddings, and vector databases
Proficiency in Python and familiarity with APIs, microservices, or backend development
Experience working with cloud-based AI services, preferably on Azure
Understanding of model evaluation, testing, monitoring, and quality improvement techniques
Familiarity with secure development practices and enterprise application integration
Strong problem-solving, communication, and collaboration skills Preferred Qualifications
Experience with Azure OpenAI Service, Azure AI Search, Azure Machine Learning, or related Azure AI services
Working knowledge of Azure DevOps, including repositories, boards, pipelines, and release workflows
Experience with Agentic-LLM solutions using LangChain, LangGraph, or similar tools
Experience with vector databases or search platforms such as Azure AI Search
Familiarity with containerization, CI/CD, and deployment automation
Experience supporting enterprise-scale AI solutions, chatbot platforms, knowledge assistants, or intelligent automation use case\"\"\"

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