Lead AI Platform Engineer

Role Description

• Build scalable, fault-tolerant cloud-native services on Microsoft Azure, ensuring high performance and reliability.
• Develop secure, well-documented public APIs and SDKs for consumption by internal and external developers.
• Collaborate with cross-functional teams to deliver end-to-end solutions across data pipelines, orchestration, and service APIs.
• Embed robust security controls to protect sensitive data and ensure secure access to AI services.
• Contribute to design reviews, code reviews, and architectural discussions to ensure engineering excellence.
• Mentor junior developers, encourage continuous learning, and contribute to a culture of innovation.
• Work with multiple teams to create AI solutions, which include AI model deployment, training, and AI tooling development.
• AI & Cloud Expertise
• Experience working with Large Language Models (LLMs) and understanding of trade-offs between performance, cost, and capability.
• Understanding of Retrieval-Augmented Generation (RAG), agent orchestration, prompt engineering, and tool calling.
• Familiarity with AI standards such as Model Context Protocol (MCP) and Agent2Agent (A2A).
• Strong knowledge or experience in working with various ML algorithms (regression, classification, clustering, deep learning)
• Knowledge of AI ethics and regulations (e.G., NIST AI RMF, EU AI Act), and commitment to responsible AI development.
• Fluent in developing code using AI Tools such as GitHub Copilot. Must be able to use prompt engineering to carry out multiple development tasks.
• Familiar with AI orchestration, including tools like AI Foundry and / or Semantic Kernel.
• Experience with tools for automated testing and evaluation of AI outputs is a plus.
• Experience in Python and AI frameworks / Tools such as PyTorch and TensorFlow.

Qualifications