Lead AI Engineer

Lead AI Engineer

Must be W2

Remote

Role:
We are seeking a highly skilled AI Engineer with strong hands-on experience in Microsoft Azure, Agentic AI architectures, and Retrieval-Augmented Generation (RAG) solutions. This role is responsible for designing, building, and deploying scalable AI systems that accelerate business performance and enhance decision-making across the organization.

• Design, develop, and implement end-to-end AI solutions leveraging Azure AI services, including Azure OpenAI, Cognitive Search, Machine Learning, and related cloud components.
• Build and optimize Agentic AI workflows, including multi-agent architectures, orchestration frameworks, and autonomous system capabilities.
• Develop RAG pipelines using vector databases, embeddings, content enrichment, and document retrieval techniques to improve relevance and model accuracy.
• Collaborate closely with data engineering, product, and architecture teams to integrate AI features into enterprise applications and platforms.
• Conduct performance optimization, model evaluation, monitoring, and quality assurance to ensure scalable and reliable AI deployments.
• Ensure solutions meet security, compliance, and governance guidelines aligned with enterprise standards.
• Stay up to date with the latest advancements in AI models, agentic systems, and Azure capabilities to proactively identify innovation opportunities.

• Proven hands-on experience with Azure AI ecosystem (Azure OpenAI, Azure ML, Cognitive Search, Azure Functions, Logic Apps).
• Strong proficiency in RAG architectures, vector search, embedding models, and LLM prompt engineering.
• Practical experience building Agentic AI workflows (multi-agent systems, decision-making pipelines, tool invocation strategies).
• Solid programming skills in Python or C# and familiarity with relevant AI/ML frameworks.
• Experience designing production-grade AI applications with an emphasis on scalability, observability, and performance.
• Strong analytical mindset with the ability to translate business needs into technical solutions.

• Experience with MLOps and Dev Ops practices on Azure.
• Knowledge of data governance, security patterns, and responsible AI principles.
• Prior experience supporting enterprise-grade digital transformation or AI modernization initiatives.