Lead Artificial Intelligence Engineer – Azure AI Foundry

Job Summary

Lead AI Engineer

Key Responsibilities

Technical Leadership

• Lead architecture, design, and implementation of AI solutions using

  Azure AI Foundry

• Design and deploy

  Generative AI, LLM-based, and ML solutions

  on Azure
• Guide teams on model selection, prompt engineering, fine-tuning, and evaluation
• Establish best practices for AI solution development, security, and scalability
• Review technical designs, code, and AI workflows

AI / ML Engineering

• Build and deploy AI models using

  Azure OpenAI, Azure Machine Learning, Azure Cognitive Services

• Develop end-to-end ML pipelines including data ingestion, training, validation, deployment, and monitoring
• Implement

  RAG (Retrieval-Augmented Generation)

  architectures
• Optimize model performance, cost, and latency
• Ensure responsible AI practices including bias detection, explainability, and governance

Platform & DevOps

• Work with

  Azure DevOps, GitHub Actions

  , and CI/CD pipelines for AI workloads
• Deploy AI solutions using containers (Docker) and orchestration tools (AKS)
• Monitor and manage AI workloads for reliability and performance
• Collaborate with cloud, data, and security teams

Team & Stakeholder Management

• Mentor and lead AI engineers and data scientists
• Collaborate with product owners, architects, and business stakeholders
• Translate business requirements into technical AI solutions
• Provide project updates, technical guidance, and risk mitigation

Required Skills & Qualifications

• 8–12+ years of experience in

  AI/ML engineering

  , with at least 3+ years in a lead role
• Strong hands-on experience with

  Azure AI Foundry

• Expertise in

  Azure OpenAI, Azure ML, Cognitive Services

• Strong programming skills in

  Python

  (preferred)
• Experience with

  LLMs, GenAI, NLP

  , and prompt engineering
• Hands-on experience with

  RAG, vector databases

  , and embeddings
• Strong understanding of

  cloud-native architecture on Azure

• Experience with

  CI/CD, MLOps

  , and model monitoring
• Excellent communication and leadership skills

Good to Have

• Experience with

  multi-cloud AI solutions

• Knowledge of

  LangChain, Semantic Kernel

  , or similar frameworks
• Experience in

  enterprise AI governance and compliance

• Microsoft Azure certifications (AI Engineer, Solutions Architect)
• Experience working with regulated industries