Business Systems Analyst - AI Automation

Avalara•UNAVAILABLE, UNAVAILABLE

About The Position

As Avalara scales its AI-first enterprise systems, workflows, and automation footprint, this role is crucial for improving the clarity, structure, and quality of requirements that drive AI automation and business transformation. The Business Systems Analyst (BSA) will translate complex business workflows into well-defined, implementation-ready requirements for AI-enabled automation, agentic workflows, and transformation initiatives. This role operates at the intersection of business process design, AI automation strategy, and technical execution, working closely with AI Automation Engineers in an environment utilizing n8n, Boomi, APIs, event-driven systems, and AI-enabled orchestration. The goal is to ensure initiatives are scalable, governed, measurable, and aligned to business outcomes, thereby strengthening Avalara’s automation and transformation ecosystem by improving requirement quality, delivery predictability, and AI automation clarity.

Requirements

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

Responsibilities

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.
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.
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.
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.
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.
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.