AI Architect

Our customer is presently seeing a skilled AI Lead/AI Architect for a Remote, Contract-to-Hire career position.

Our customer’s platform is Microsoft Azure. This is a high-impact, highly visible role that combines deep technical architecture, hands-on implementation, and vendor oversight. The hired candidate must have the technical authority to ensure everything our customer builds, and everything their vendors build, and ensure they come together as one unified, production-grade AI system.

Responsibilities:

• Design and own the enterprise AI platform architecture within Azure AI Foundry and the broader Microsoft Azure ecosystem, serving as the technical authority across all AI initiatives
• Define a unified AI platform blueprint — including agent orchestration, tool/function calling, memory management, and API integration patterns — that all internal teams and external vendors must build toward
• Serve as the primary technical authority over all external AI vendors, reviewing deliverables, enforcing architectural standards, and ensuring all vendor-built components integrate into one cohesive platform
• Take a hands-on role in building, deploying, and remediating AI solutions — particularly during platform build-out or when vendor work requires direct intervention
• Design and build multi-agent systems — including agent hierarchies, task delegation, inter-agent communication, and autonomous reasoning workflows using frameworks such as Semantic Kernel or AutoGen
• Develop and deploy custom AI agents, copilots, and automated workflows using Microsoft Copilot Studio and Azure AI Foundry
• Collaborate with the API Integration Manager to ensure AI agents and services are properly connected and aligned to enterprise systems, providing architectural guidance and AI-specific requirements as needed
• Design and implement RAG pipelines including document ingestion, embedding models, chunking strategies, and retrieval configuration using Azure AI Search or equivalent vector stores
• Lead the build-out and ongoing operation of the AI Center of Excellence (CoE), defining standards, reference architectures, reusable agent components, and governance frameworks
• Establish and enforce responsible AI and data governance practices — covering PII handling, content filtering, bias mitigation, access controls, and compliance across all AI workloads
• Implement agent monitoring and observability across production deployments, including performance tracking, reasoning trace review, failure detection, and continuous improvement
• Facilitate AI use case identification and prioritization by partnering with business stakeholders across the organization to assess feasibility and business value
• Translate complex AI architecture decisions into clear, business-relevant communication for senior leadership and non-technical stakeholders
• Mentor and develop internal AI/ML engineers and data scientists, elevating overall team capability and fostering a culture of innovation
• Stay current on the evolving agentic AI landscape and advise leadership on emerging tools, frameworks, and Azure capabilities relevant to the business roadmap

Education/Experience:

• Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, or a related field
• 7+ years of experience in AI/ML engineering or architecture, with at least 3 years in a lead or architect-level role
• Proven hands-on experience with Azure AI Foundry in a production environment, specifically building and deploying agentic AI solutions — this is a core requirement
• Deep working knowledge of Azure OpenAI Service, Azure Machine Learning, Azure API Management, and the broader Microsoft Azure platform
• Hands-on experience with Microsoft Copilot Studio building custom copilots, agents, and AI-powered automations
• Strong experience designing and building multi-agent systems using frameworks such as Semantic Kernel, AutoGen, or LangChain — including agent orchestration, tool/function calling, and memory and state management
• Strong experience designing and implementing RAG architectures and working with vector databases such as Azure AI Search, Pinecone, or Weaviate
• Advanced proficiency in prompt engineering for agentic workflows — including chain-of-thought, ReAct patterns, and system prompt design for autonomous reasoning
• Proven track record of managing multiple external vendors on concurrent AI development projects and aligning their outputs to a unified platform
• Experience building or leading an AI Center of Excellence (CoE) or equivalent AI governance and enablement function
• Experience with agent observability and monitoring — reasoning trace analysis, failure detection, and performance evaluation in production environments
• Familiarity with MLOps practices including CI/CD for AI, model versioning, and deployment pipelines is a plus
• Familiarity with Microsoft Fabric and its integration with AI workloads is a strong plus
• Microsoft certifications such as Azure AI Engineer Associate (AI-102) or Azure Solutions Architect Expert are preferred
• Experience in manufacturing, e-commerce, or distribution/supply chain environments is a plus but not required