Enterprise AI Architect

Role: Enterprise AI Architect (Senior Principal)

Location: Cincinnati, Ohio

Employment Type: Permanent

Key Skills: Architecture Governance, Business Process Design, Mapping, Capability Models, EA Frameworks, Reference Architecture, Research, Papers, Enterprise Roadmap / Strategy, Transformation.

Key Responsibilities:

AI Strategy & Architecture

• Evaluate existing AI frameworks, platforms, and governance models to identify strengths, weaknesses, and gaps.
• Align AI initiatives with business goals, data governance policies, and IT infrastructure.
• Recommend enhancements to AI architecture, tools, and integration strategies.
• Assess and propose suitable AI platforms, tools, and frameworks for enterprise adoption.

AI Solution Design

• Develop end-to-end AI reference architectures including data models, agentic workflows, orchestration, security, and observability.
• Design agentic flow architectures for autonomous task execution and business workflow transformation.
• Architect AI agents for AIOps and intelligent operations.
• Collaborate with engineering and operations teams to integrate AI solutions into enterprise systems.

Governance & Compliance

• Ensure AI solutions comply with enterprise governance, security, and ethical standards.
• Establish best practices for responsible AI and model explainability.
• Define observability standards including tracing, logging, and performance monitoring using tools like LangFuse or Arize Phoenix.

Innovation & Thought Leadership

• Stay abreast of emerging AI technologies and recommend adoption strategies.
• Foster a culture of experimentation, learning, and responsible AI.
• Mentor junior team members and aspiring architects.

Key Requirements for the Position

• Proven experience in designing and implementing enterprise-grade AI solutions.
• Expertise in building agentic systems and intelligent automation for operations and SDLC.
• Strong understanding of AI governance, security, and compliance frameworks.
• Experience in integrating AI with enterprise systems and external APIs.

Key Skills

• AI/ML Platforms & Cloud Services: Azure, GCP, OpenAI, Anthropic, LLaMA.
• Agent Frameworks & Orchestration: LangGraph, LangChain, workflow design.
• State & Memory Management: Persistent state handling, vector databases (e.g., Pinecone, Weaviate, Chroma).
• Prompt Engineering: Reusable prompts, guardrails, system instructions.
• Knowledge Retrieval: Embedding models, RAG, GraphRAG.
• Tool Integration: External APIs, enterprise systems, custom tools.
• MLOps/LLMOps: CI/CD for models, prompt versioning, lifecycle management.
• Observability Tools: LangFuse, Arize Phoenix.
• Containerization & DevOps: Docker, Kubernetes, CI/CD pipelines.
• Knowledge Fabric & AI Fabric: Semantic modeling, contextual AI enablement, knowledge graphs.

Qualification Criteria

• Bachelor’s or master’s degree in computer science, Data Science, AI/ML, or related field.
• Minimum 10 years of experience in enterprise architecture, with at least 5 years in AI/ML solutioning.
• Demonstrated experience in designing AI agents and intelligent automation solutions.
• Strong communication, strategic thinking, and stakeholder management skills.
• Ability to work cross-functionally and influence decision-making.