Sr. AI/ML Engineer

Role & responsibilities

• Develop and implement

  enterprise-grade LLM-based applications (e.g., RAG, agents, and copilots) using Azure OpenAI, LangChain, and Semantic Kernel.

• Write high-quality, maintainable, and efficient code

  in Python, including data processing scripts (potentially with PySpark) and API endpoints.

• Build and optimize

  RAG (Retrieval-Augmented Generation) pipelines, integrating vector search capabilities using Azure Cognitive Search, FAISS, or similar technologies.
• Collaborate with AI Architects and Product Owners to translate requirements and architectural designs into technical specifications and working code.

• Implement and manage MLOps pipelines

  for model deployment, monitoring, and lifecycle management using Azure Machine Learning, Azure DevOps, and GitHub Actions.

• Integrate AI models and services

  with other business applications and data sources using Azure Functions, APIM, Logic Apps, and Service Bus.
• Implement robust testing, debugging, and performance tuning for AI applications to ensure scalability and reliability.

• Mentor junior developers,

  conduct regular code reviews, and promote development best practices (e.g., TDD, clean code).
• Stay current with the latest Azure AI services and Generative AI techniques, experimenting with new tools and frameworks to drive innovation.

Preferred candidate profile

• 8+ years

  of overall IT experience, with

  3-4+ years

  in a hands-on AI/ML or software development role.
• Proven, hands-on development experience with:
• Azure OpenAI Service and Azure AI Studio
• LLM Orchestration frameworks (LangChain, Semantic Kernel)

• Expert-level Python

  programming
• Vector databases (e.g., Azure Cognitive Search, FAISS) and implementing RAG patterns
• Strong, practical experience with

  MLOps on Azure

  , including CI/CD pipelines (Azure DevOps, GitHub Actions) and Azure Machine Learning.
• Solid experience with Azure data and integration services (e.g.,

  Azure Data Lake, Azure Functions, API Management, Logic Apps

  ).
• Strong understanding of LLM fundamentals, prompt engineering, and fine-tuning techniques.
• Strong problem-solving, debugging, and analytical skills.
• Experience working in Agile/Scrum development environments.
• Excellent communication skills and a collaborative, team-oriented mindset.