Agentic Workflow Engineer

The Agentic Workflow Engineer is responsible for designing, developing, analyzing, and implementing AI-enabled workflows and agentic solutions that optimize institutional business processes to support the growth, service level, productivity, and cost performance needs of the university.

The AWE's primary focus is to reimagine how work gets done by combining agentic AI, workflow automation, systems integration, and business process engineering to improve operational efficiency and enable scalable, data-driven execution.

Responsibilities:

• Designs, develops, tests, and implements AI-enabled workflows and agentic solutions to improve complex business processes within and across multiple business units.
• Partners with executives, vice presidents, senior leaders, and cross-functional stakeholders to translate institutional strategy and business priorities into high-value AI-enabled transformation opportunities, future-state operating models, and measurable outcomes.
• Identifies and prioritizes enterprise transformation opportunities aligned with institutional strategy and business priorities, redesigning work using agentic AI, workflow orchestration, conventional automation, and human-in-the-loop decision-making to improve productivity, service levels, quality, cost performance, and deliver measurable business value.
• Translates business requirements and process improvement opportunities into technical designs, executable AI tasks, multi-step agent workflows, working prototypes, and scalable workflow solutions.
• Designs responsible AI solutions, determining appropriate levels of autonomy, agent authority, human verification and approval, exception handling, escalation, access controls, and monitoring based on business impact and risk.
• Develops and integrates AI agents with approved enterprise applications, APIs, MCP-enabled tools, data sources, and business systems to enable coordinated execution of multi-step workflows.
• Applies programming, automation, AI-assisted development, and software engineering practices to build, debug, evaluate, and continuously improve solutions.
• Analyzes current-state processes, identifies inefficiencies and unnecessary work, and engineers future-state workflows that optimize the interaction between people, processes, and technology.
• Establishes testing and evaluation approaches to measure solution accuracy, reliability, performance, and effectiveness across standard, edge-case, ambiguous, and failure conditions.
• Collaborates with IT, Systems Engineers, Enterprise Architects, Product Managers, and other technology partners to align solutions with enterprise architecture, security, integration, and production requirements.
• Develops measurement plans and tracks business and AI-specific key performance indicators (KPIs) and Objectives & Key Results (OKRs) to demonstrate realized value, including capacity improvements, reduced manual effort, service-level performance, exception rates, human intervention, workflow reliability, and cost efficiency in partnership with Finance.
• Establishes reusable engineering patterns, technical standards, and implementation practices to accelerate the development and adoption of AI-native workflows across Business Process Engineering.
• Coaches and supports other team members and university employees in the application of AI-enabled workflow engineering and process transformation practices.
• Supports enterprise-level process and cultural transformation, partnering with stakeholders across organizational levels, to guide stakeholders through changes to roles, responsibilities, and ways of working.
• Constructs and communicates solution designs, project status, risks, and business outcomes to technical and non-technical stakeholders at all levels of the organization.
• Collaborates with professionals across the university to identify emerging technologies and opportunities that advance the institution's strategic objectives and student-obsessed mission.
• Responds with urgency to organizational needs, exercises sound technical and business judgment, and takes accountability for delivering measurable results.
• Works in conjunction with Finance and business stakeholders to quantify transformation opportunities, develop business cases, demonstrate expected and realized value, capacity, service levels, outcomes, and cost over time to identify opportunities and prevent operational inefficiencies.

Qualifications:

• Bachelor's degree in computer science, Software Engineering, Information Systems, Industrial Engineering, Operations Research, or another relevant engineering, business, or technical discipline
• 5 years of related experience in software development, AI-enabled solutions, workflow automation, systems integration, or business process engineering.
• Knowledge of applied artificial intelligence, large language models (LLMs), agentic AI concepts, and their application in business workflow transformation.
• Proficiency in programming and software development fundamentals, including the ability to develop, debug, and maintain working solutions using languages such as Python.
• Knowledge of APIs, MCPs, system integration, data structures, and workflow orchestration to connect AI agents with enterprise applications and approved data sources.