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We need an AI Engineer with depth and breadth across the AI space and a strong command of Azure. You’ll bring hands-on GenAI expertise but know when NLP, computer vision, classical ML, or data pipelines are the better fit. You’ll build practical, scalable AI solutions on Azure across the full lifecycle—data prep to deployment. We want proactive people who take ownership and drive initiatives beyond day-to-day coding.
Job Responsibility:
Build and integrate AI models using Azure ML, Cognitive Services, and Azure OpenAI Service
Drive MLOps using Azure ML pipelines, Azure DevOps, and CI/CD workflows
Handle data preparation (cleaning, preprocessing, validation) with Azure Data Factory and Databricks
Write clean, reusable code following Azure cloud-native best practices
Build APIs and prototypes
deploy via AKS or Azure Functions
Collaborate with data engineers, developers, and product owners
Drive experiments, contribute ideas, and shape solution approaches
Stay current with GenAI and broader AI developments
apply Azure-native capabilities
Requirements:
Solid AI/ML foundation with hands-on GenAI experience (development, integration, evaluation)
Strong Azure AI skills: Azure ML, Azure OpenAI Service, Cognitive Services, AI Search
Familiarity with NLP, computer vision, recommendation systems, and classical ML
Experience with PyTorch, TensorFlow, or Scikit-learn
Exposure to agentic AI frameworks (LangChain, LlamaIndex, CrewAI, Agno)
Proficiency with Azure Databricks, Data Factory, Synapse Analytics, and Data Lake Storage
Strong data handling skills (exploration, cleaning, preprocessing)
Ability to prototype quickly and build APIs using Azure Functions or App Service
Must actively use AI-assisted development tools (GitHub Copilot, Cursor, Claude Code, etc.)
Strong problem-solving and communication skills
Nice to have:
Real-world AI project experience in an Azure cloud environment
Curiosity to explore new tools, frameworks, and problem domains
Experience with financial projects or large enterprise environments