• Partner with stakeholders and AI Automation Engineers to gather, analyze, and document AI automation requirements that reduce ambiguity and downstream rework

• Map and document current-state and future-state processes, identifying transformation opportunities where AI, agents, or workflow automation can improve speed, quality, or scale

• Break down complex workflows into structured, implementable use cases, including decision points, exceptions, approvals, and human-in-the-loop steps

• Identify risks, edge cases, control requirements, and system dependencies before automation development begins

• Create and manage JIRA tickets with detailed requirement descriptions, acceptance criteria, dependencies, and traceability to ensure smooth development, tracking, and delivery of AI automation initiatives

AI Integration-Focused Solution Definition

• Translate business needs into clear functional and technical requirements for AI-enabled workflows, agents, and transformation solutions

• Define system interactions, API touchpoints, event triggers, workflow boundaries, and handoffs between deterministic automation and AI decisioning

• Create detailed user stories, business rules, and acceptance criteria that are implementation-ready for AI Automation Engineers

• Collaborate with architects and AI Automation Engineers to validate feasibility, governance, and solution design before build begins

Data & Interface Analysis

• Analyze data flows across systems and document transformation, validation, and context requirements needed for AI automation outcomes

• Define field-level mappings, prompt and input requirements, exception scenarios, auditability needs, and reconciliation rules to protect data integrity and trust

• Support A2A, MCP, API contract reviews and ensure traceability between business objectives, workflow behavior, and technical implementation

Delivery Enablement & Collaboration

• Participate in backlog grooming and sprint planning to maintain requirement clarity for AI automation and transformation initiatives

• Support testing and UAT validation to ensure AI-enabled workflows behave as intended across normal, exception, and human-review scenarios

• Facilitate alignment between stakeholders, AI Automation Engineers, architects, and delivery teams

• Maintain structured documentation to support auditability, governance, adoption, and long-term maintainability

Governance & Continuous Improvement

• Standardize requirement templates and documentation practices for AI automation, agents, and transformation initiatives

• Support change management for workflow, model, prompt, and automation enhancements

• Improve requirement quality and automation maturity across the organization

• Drive clarity that accelerates responsible AI adoption and improves overall delivery predictability

12-Month Success Signals

Within the first 12 months, this role will have:

• Reduced automation rework and requirement-related defects

• Improved implementation readiness of AI automation stories, business rules, and acceptance criteria

• Established standardized documentation templates adopted across AI automation and transformation initiatives

• Increased automation throughput by reducing requirement ambiguity and improving stakeholder alignment

• Improved traceability between business objectives and delivered AI automation outcomes

AI Expectations

As an AI-first company, Avalara expects this role to embed AI into requirements analysis, process transformation, and automation strategy.

This role will:

• Identify AI and automation opportunities within business workflows that improve efficiency, decision quality, and scalability

• Use AI tools to accelerate documentation drafting, process analysis, impact assessment, and requirement validation

• Ensure AI-enabled workflows, agents, and human-in-the-loop controls are documented with clear governance and traceability

• Partner with AI Automation Engineers and architects to define measurable AI-driven outcomes, evaluation criteria, and business impact

• Apply AI responsibly with attention to data privacy, security, compliance, and operational risk

Demonstrating applied AI impact, not just tool familiarity is required.

What You Bring

• B.S. in Computer Science or Engineering (required)

• 5+ years of experience as a Business Systems Analyst or Techno-Functional Analyst

• Experience working with AI automation, enterprise workflows, system integrations, APIs, n8n, Boomi, or automation platforms

• Strong understanding of Agentic AI, REST APIs, webhooks, JSON, data mapping concepts, and workflow orchestration patterns

• Experience documenting requirements for automation, AI-enabled workflows, system interactions, and business process transformations

• Ability to interpret technical design documents and collaborate effectively with AI Automation Engineers, architects, and cross-functional stakeholders

• Strong analytical and structured problem-solving skills

• Excellent communication skills across business and technical audiences