Business Systems Analyst - AI Automation

Avalara

1d•Remote

About The Position

As Avalara scales its AI-first enterprise systems, workflows, and automation footprint, we must improve the clarity, structure, and quality of requirements that drive AI automation and business transformation across the organization. This role exists to translate complex business workflows into well-defined, implementation-ready requirements for AI-enabled automation, agentic workflows, and transformation initiatives that improve solution quality, shorten delivery cycles, and accelerate measurable business value. This BSA will operate at the intersection of business process design, AI automation strategy, and technical execution, working closely with AI Automation Engineers in an environment centered on n8n, Boomi, APIs, event-driven systems, and AI-enabled orchestration to ensure initiatives are scalable, governed, measurable, and aligned to business outcomes. This role strengthens Avalara’s automation and transformation ecosystem by improving requirement quality, delivery predictability, and AI automation clarity. As a Bar Raiser, this role is expected to elevate automation maturity across the organization by holding high standards for clarity, documentation quality, traceability, and business process rigor; using structured analysis and data to reduce ambiguity, automation failure points, and downstream rework; challenging unclear requirements early to protect delivery timelines and automation quality; sharing best practices and improving requirement documentation standards for AI automation and transformation initiatives; and leaving processes, playbooks, and requirement frameworks stronger and more scalable than they were before.

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