AI Engineer

• Develop RAG architectures that connect LLMs to enterprise documents, databases, APIs, and other data sources.
• Design and implement vector search, embeddings, semantic search, and knowledge retrieval capabilities.
• Develop AI workflows using frameworks such as Semantic Kernel, LangChain, LangGraph, or Microsoft Copilot Studio.
• Integrate AI solutions with existing enterprise applications, APIs, databases, and data platforms.
• Develop production-quality services using Python and/or .NET/C#.
• Work with Azure services including Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, Azure Storage, and related cloud services.
• Build data pipelines and preprocessing workflows to prepare enterprise information for AI applications.
• Evaluate LLM performance, accuracy, relevance, latency, and cost.
• Implement techniques such as prompt engineering, grounding, retrieval optimization, evaluation, and guardrails.
• Partner with data engineers, software engineers, architects, and business stakeholders to move AI initiatives from proof-of-concept to production.
• Establish appropriate practices for security, responsible AI, data privacy, and governance.
• Troubleshoot and optimize AI applications in production environments.
• Stay current with emerging AI technologies, models, frameworks, and development practices.

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent professional experience.
• 3+ years of software engineering, data engineering, machine learning, or AI development experience.
• Hands-on experience building and deploying Generative AI or LLM-powered applications.
• Strong Python and/or C#/.NET development experience.
• Experience with Azure cloud services and enterprise application development.
• Experience working with Azure OpenAI, Azure AI Foundry, or comparable LLM platforms.
• Strong understanding of RAG architectures, embeddings, vector databases, and semantic search.
• Experience integrating AI solutions with APIs, databases, enterprise applications, or other data sources.
• Experience with at least one AI orchestration framework such as Semantic Kernel, LangChain, LangGraph, or Copilot Studio.
• Understanding of software development practices including Git, CI/CD, testing, APIs, and application deployment.
• Experience with Microsoft Fabric, Power BI, or Copilot.
• Experience with Azure AI Search or other vector search technologies.
• Experience building enterprise AI agents and agentic workflows.
• Experience with SQL, data engineering, ETL/ELT, and cloud data platforms.
• Experience with Databricks, Snowflake, or similar modern data platforms.
• Experience with MLOps, LLMOps, model evaluation, or AI observability.
• Experience integrating AI with ERP, CRM, HRIS, document management, or other enterprise systems.
• Knowledge of authentication, authorization, API security, and enterprise data governance.
• Experience taking AI solutions from POC/prototype through production deployment. Technology Doesn’t Change the World, People Do.®

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