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.
What You’ll Work On
- 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.
What We Value
- 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.
Preferred:
- 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.
