AI Process Architect

Role: AI Process Architect

Job Summary
Seeking candidates with a Business Analyst and Product Management background. Must have a deep understanding of AI (how processes are converted into an AI perspective).  The architect will work with Product Developers who interact with Business Stakeholders. The APA will meet with PD's and Stakeholders to document and make recommendations.

Key Responsibilities

• Stakeholder Engagement & Discovery: Collaborate directly with business stakeholders and operational teams to deeply understand their daily workflows, pain points, and strategic objectives.
• Process Analysis & AI Suitability: Evaluate existing business operations to determine if they are viable candidates for Generative AI or Agentic integration, weighing potential efficiency gains against technical feasibility and risk.
• AI Solution Design: Architect the "future state" of automated workflows, mapping out conceptual AI agent interactions, human-in-the-loop touchpoints, and data flows to guide the engineering team.
• Technical Translation: Act as the critical bridge between business units and AI developers, converting complex business logic into clear technical requirements, user stories, and system architectures.
• Performance Evaluation & Change Management: Define success metrics for newly implemented AI workflows, monitoring user adoption, mitigating workflow bottlenecks, and ensuring the AI solution actually solves the intended business problem.

• Business Analysis & Process Mapping: Advanced proficiency in process modeling techniques and tools (e.g., Lucidchart, Visio) to clearly map current states, future states, and decision trees.
• Applied AI Literacy: Strong conceptual understanding of Generative AI capabilities, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic workflows, including their limitations (e.g., hallucinations, context windows).
• Prompt Engineering & Prototyping: Practical experience drafting, testing, and refining system prompts to validate business use cases before handing them off for full-scale software development.
• Cross-Functional Communication: Exceptional ability to translate highly technical AI concepts to non-technical business audiences, while firmly and clearly communicating business needs back to engineering teams.
• Requirements Gathering & Documentation: Proficiency in Agile methodologies, managing project backlogs, and writing detailed, robust technical documentation and acceptance criteria.