Enterprise AI Architect

The AI Enterprise Architect will design, develop, and lead enterprise AI and intelligent automation solutions across the organization. This role will partner with business stakeholders, application teams, enterprise architecture, infrastructure, and cybersecurity teams to define scalable AI strategies and deliver intelligent solutions that improve business capabilities, operational efficiency, and decision-making. The ideal candidate combines strong enterprise architecture expertise with hands-on experience in Generative AI, enterprise AI platforms such as ChatGPT Enterprise and Claude, MCP/server-based AI integrations, Azure AI Foundry, cloud technologies, AI governance, and enterprise application integration., * Design and architect enterprise AI and intelligent automation solutions leveraging Azure AI Services, Azure AI Foundry, OpenAI, Microsoft Fabric, and cloud-native technologies.

• Lead the implementation of Generative AI, LLMs, Retrieval-Augmented Generation (RAG), AI agents, copilots, and workflow automation solutions.
• Design and implement MCP (Model Context Protocol) servers, reusable AI integration frameworks, and secure connectivity patterns that connect enterprise AI platforms with internal systems, APIs, and data sources.
• Collaborate directly with business users to co-create and refine custom Skills, GPTs, and AI agents, translating business requirements into effective AI solutions and empowering users with self-service capabilities.
• Establish and lead enterprise AI architecture and governance frameworks, including responsible AI standards, model and prompt governance, security controls, compliance, monitoring, lifecycle management, and AI risk management practices.
• Develop proof-of-concepts, prototypes, and reference architectures for AI-powered business solutions.
• Provide architectural leadership and technical guidance for AI orchestration, prompt engineering, embeddings, vector search, and enterprise AI integration patterns.
• Collaborate with infrastructure, cybersecurity, application development, and data teams to support enterprise AI platform readiness and operational support.
• Evaluate emerging AI technologies, MCP standards, governance models, and enterprise platforms to support the organization’s AI strategy and roadmap.
• Leverage AI-assisted development tools such as GitHub Copilot, Claude, GPT, or similar technologies to improve engineering efficiency and solution quality.

• Experience in enterprise solution architecture, software engineering, cloud architecture, or AI/ML engineering roles.
• Hands-on experience designing and implementing AI, machine learning, or Generative AI solutions in enterprise environments.
• Strong expertise with Azure cloud and AI technologies including Azure OpenAI, Azure AI Foundry, Azure AI Services, Azure Functions, AKS, Azure Storage, and API Management.
• Hands-on experience with Azure AI Foundry including prompt flows, AI agents, evaluations, and AI lifecycle management.
• Experience designing and implementing Retrieval-Augmented Generation (RAG), vector search, embeddings, prompt engineering, and AI agent orchestration solutions.
• Experience designing and developing MCP (Model Context Protocol) servers, AI integration services, or similar middleware frameworks for enterprise AI platforms.
• Experience integrating LLM platforms with enterprise APIs, databases, document repositories, and business applications.
• Experience implementing enterprise AI governance, responsible AI frameworks, security controls, and compliance practices.
• Understanding of enterprise security architecture, data privacy, access controls, and regulatory considerations for AI platforms in financial services environments.
• Hands-on experience with Python, REST APIs, SDK integrations, automation frameworks, and CI/CD practices.

• Financial services or asset management industry experience is preferred.

• Strong understanding of Generative AI, LLM orchestration, prompt engineering, AI agents, MCP integration patterns, and enterprise AI workflows.
• Knowledge of Azure AI Foundry capabilities including prompt flows, AI agents, model evaluations, safety controls, and AI governance.
• Strong understanding of API integrations, cloud-native architecture, distributed systems, and enterprise application integration patterns.
• Knowledge of enterprise AI governance, responsible AI practices, AI security, privacy, model governance, and AI risk management.
• Understanding of vector databases, semantic search, embeddings, and enterprise AI retrieval patterns.
• Familiarity with AI orchestration frameworks and libraries such as LangChain, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
• Familiarity with vector databases and enterprise search platforms such as Pinecone, Azure AI Search, Weaviate, ChromaDB, or similar technologies.
• Relevant cloud, AI, governance, or architecture certifications such as Azure Solutions Architect Expert, Azure AI Engineer Associate, TOGAF, or equivalent certifications are preferred.
• Strong analytical, communication, presentation, documentation, and problem-solving skills.
• Ability to communicate complex AI concepts to both technical and non-technical stakeholders.
• Comfort leveraging AI-assisted development tools such as GitHub Copilot, Claude Code, ChatGPT, or similar platforms to improve development productivity and solution delivery., Bachelor’s degree in Computer Science, Information Systems, Artificial Intelligence, Engineering, or a related field.

Job DescriptionOur client a leading asset management firm, located in New York City is looking to hire an Enterprise AI Architect. This is a Full Time Position. Citizens and those authorized to work in the U.S. are encouraged to apply. We are unable to sponsor at this time. Qualified candidates should send their resumes (Word Format) along with salary expectations to Daniel@velocitysgi.com .