Agentic AI Data Architect

Update: one thing the client is looking for is Azure Data Factory experience for this AI Data Architect. this is a competitive backfill for us and we can win this fairly easily with some solid folks. Top 3 skills we’re looking for are: 1. Agentic AI Architecture at an Enterprise level 2. Data Architecture/Engineering exposure. 3. Azure Data Factory (Azure is the environment), We are seeking an experienced Agentic AI Data Architect to design, build, and deploy AI-powered applications that automate business processes and improve decision-making. This is a hands-on technical leadership role focused on developing production-ready AI solutions using large language models (LLMs), agentic AI frameworks, retrieval-augmented generation (RAG), and modern cloud data platforms., * Design and build agentic AI applications that automate business workflows and improve operational efficiency.

• Develop AI solutions using LLMs, multi-agent architectures, and retrieval-augmented generation (RAG).
• Create and optimize prompt engineering strategies, reasoning workflows, and AI integrations.
• Build and maintain APIs, backend services, and AI application components.
• Evaluate new AI technologies and recommend solutions that drive business value. Data Architecture & Integration
• Design data retrieval and grounding strategies that connect AI applications to enterprise data sources.
• Develop vector search, embedding, and knowledge retrieval solutions.
• Partner with data engineering teams to ensure AI systems leverage reliable and secure data pipelines.
• Establish standards for AI performance, accuracy, and reliability. Technical Leadership
• Serve as a technical lead for AI architecture and development initiatives.
• Provide guidance and mentorship to developers, engineers, and technical teams.
• Review solution designs and help establish AI development standards and best practices.
• Translate complex AI concepts into practical solutions for technical and business stakeholders. Platform & Automation
• Support and enhance enterprise AI platforms and integrations.
• Implement automation, CI/CD, and Infrastructure-as-Code (IaC) practices for AI deployments.
• Maintain technical documentation, architecture diagrams, and implementation standards. Required Qualifications, * Delivery of scalable, production-ready AI applications.
• Ability to move AI use cases from concept to deployment.
• Technical leadership and mentorship of engineering teams.
• Quality, reliability, and business impact of AI solutions.
• Effective collaboration with engineering, data, and business stakeholders

The ideal candidate will have a strong background in AI application development, data architecture, and software engineering, along with the ability to guide teams and establish best practices for enterprise AI adoption., * 8 years of experience in software engineering, data engineering, AI/ML, or related technical fields.

• 2 years of hands-on experience building and deploying AI or LLM-based applications.
• Strong experience with OpenAI, Claude, or similar LLM platforms and APIs.
• Experience building agentic AI solutions and multi-agent workflows.
• Strong understanding of prompt engineering, tool usage, and AI application design.
• Experience designing and implementing RAG solutions and vector search technologies.
• Proficiency in Python and API development.
• Experience working with cloud platforms and modern data architectures.
• Strong communication, leadership, and problem-solving skills. Preferred Qualifications
• Experience with MCP (Model Context Protocol) and agent orchestration frameworks such as LangGraph, LangChain, CrewAI, or AutoGen.
• Experience with Databricks, Snowflake, Azure AI services, or similar platforms.
• Background in workflow automation, analytics, pricing, sales, or customer-facing business applications.
• Experience working in regulated enterprise environments.
• Advanced degree in Computer Science, Data Science, AI, or a related field.

** Technical Environment Experience with the following technologies is highly desirable:**

• OpenAI, Azure OpenAI, Claude
• MCP (Model Context Protocol)
• Python, FastAPI
• LangChain, LangGraph, CrewAI
• Databricks, Delta Lake
• Vector databases and semantic search platforms
• Azure, AWS, or other cloud environments
• CI/CD pipelines and Infrastructure as Code (Terraform, GitHub Actions, Azure DevOps)