Business Analyst

Crowe's AI Y-Hire practice moves from foundational skills — requirements support, artifact creation, learning the craft — toward independent ownership of complex engagements. The AI Business Analyst operates at an experienced level, applying established business analysis skills across complex engagements while leveraging AI-enabled ways of working.

At the entry level, a BA supports elicitation, assists with testing, and follows established standards. At this level, you lead elicitation, own testing programs, and extend standards to account for what AI-augmented delivery requires. This role expands traditional business analysis responsibilities by incorporating AI-enabled analysis, documentation, and delivery practices. In this role, you will facilitate workshops, synthesize information using AI-enabled tools, and translate insights into actionable deliverables that support project outcomes.

About the role

The AI Business Analyst at Crowe translates business needs into clear, actionable requirements for AI solutions, automation platforms, and development teams. This means applying business analysis fundamentals — elicitation, documentation, testing — through an AI-first operating mode. You will use Gen AI tools including Claude Code as active instruments of analysis: interrogating process mining output to draft automation opportunity backlogs, generating first-pass test plans from acceptance criteria, and using LLM analysis to surface requirement gaps before they reach development. You will be responsible for delivering high-quality work products from discovery through user acceptance testing and implementation readiness.

Operating from India, you will work in close partnership with US-based teams across client engagements in process optimization, Hyperautomation, and Gen AI solution delivery

Responsibilities

Discovery & Analysis

1. Lead structured discovery workshops with client stakeholders — using AI tools in session to capture, synthesize, and reflect back current-state processes, pain points, and desired outcomes in real time; produce structured outputs before the debrief

2. Conduct process and task mining analysis using Microsoft Process Mining, Celonis, or equivalent platforms to surface high-ROI automation opportunities; translate event-log insights into prioritized opportunity backlogs with quantified business impact.

3. Analyze UX feedback, job aids, procedures, and existing process maps to identify candidates for further optimization; summarize findings and present recommendations with supporting data.

4. Proactively identify, analyze, and resolve requirement risks, gaps, and ambiguities — using LLM-assisted cross-reference of documentation to catch inconsistencies before they reach development; partner with stakeholders to resolve issues and appropriately escalate matters when additional guidance or decisions are required.

Requirements & Solution Design

5. Elicit and document business, user, functional, and non-functional requirements with sufficient detail to support effective implementation of AI-enabled and traditional technology solutions including decision logic, tool invocations, exception handling, and appropriate human review and oversight checkpoints

6. Translate requirements into the full artifact set: user stories, acceptance criteria, process flows, wireframes, data models, swimlane diagrams, and state diagrams — using AI-assisted tooling to accelerate first-draft creation and human judgment to validate and re

fine.

7. Design Target Operating Models that show how people, AI agents, and automated processes interact in the future state — including role evolution, governance guardrails, and escalation paths that keep humans accountable for outcomes

8. Use AI coding and analysis assistants (Claude Code, Codex, Copilot Cowork) as a productivity layer: generate first drafts of plans, criteria, models, and documentation; ensure all deliverables meet quality, accuracy, and business requirements

Delivery & Backlog Management

9. Own requirements traceability end-to-end and maintain alignment between business requirements, solution design, testing activities, and expected business outcomes; maintain documentation throughout the project lifecycle to reflect evolving business needs and decisions

10. Lead backlog organization, refinement, and work item maintenance using Crowe-standard Agile tooling (Azure DevOps or equivalent) — ensuring stories are sprint-ready, acceptance criteria are complete, and the backlog reflects current business priorities at all times.

11. Build and execute structured testing programs — functional, integration, regression, performance, and usability — for Gen AI solutions from first prototype through production handoff; prepare test plans and scripts with enough specificity that a QA engineer can execute them without clarification.

12. Facilitate and lead User Acceptance Testing (UAT): coordinate test cycles with client teams, manage defect triage, and own sign-off on solution readiness

Communication, Standards & Practice Development.

13. Build audience-calibrated presentation materials and present findings, recommendations, and ROI narratives to executives, operational leads, and end users — adjusting depth and framing without losing substance or precision

14. Apply and uphold Crowe BA standards, templates, and best practices; identify where AI-augmented delivery requires those standards to evolve and contribute to their improvement.

15. Actively develop your own practice — through emerging AI tooling, peer feedback, and client exposure — and share what you learn with the broader BA community at Crowe.

Qualifications

Required:

• 1 - 3 years in business analysis, process optimization, or hyperautomation delivery with direct exposure to AI/ML or Gen AI solution delivery (process automation, workflow design, API integration, agentic AI)
• Demonstrated daily use of Gen AI tools - Claude Code, Codex, Copilot Cowork, or equivalent; demonstrated experience applying these tools to support business analysis, documentation, process improvement, or solution delivery (portfolio examples, project references, or other examples welcome
• Full requirements artifact ownership — proven track record producing the complete artifact set: user stories, acceptance criteria, process flows, wireframes, data models, and traceability matrices for software or AI-powered solution delivery
• Agile delivery fluency — user story authoring, sprint facilitation, backlog refinement, and acceptance criteria definition in Azure DevOps, Jira, or equivalent
• Risk and gap analysis — ability to identify and address requirement inconsistencies, dependencies, risks, and scope considerations throughout the delivery lifecycle.
• English communication at full professional proficiency** — written precision and spoken clarity enabling peer-level dialogue with US-based executives and technical leads across time zones, within a global delivery environment

Foundational

• Bachelor’s degree in business, Information Systems, Computer Science, Engineering, or a related field; equivalent experience considered.
• Analytical mindset with the ability to break down complex, ambiguous problems into structured, actionable components
• Willingness to maintain a core overlap window of approximately 6:30 PM – 12:30 AM IST for US Central/Eastern

Preferred

• 1 - 3 years with process or task mining platforms (Microsoft Process Mining, Celonis, Minit,
• Apromore) CBAP, CCBA, PMI-PBA, or Agile-related certification (CSPO, IIBA-AAC)
• Prior experience in professional services, consulting, or client-facing delivery where your work is directly visible to the client
• Familiarity with BPMN, swimlane diagrams, data flow diagrams, use case modeling, and AI-assisted diagramming tools (Lucidchart, Miro, Visio)
• Exposure to testing methodologies across the full spectrum: unit, integration, regression, performance, and usability

Ideal Candidate Profile

• Strong candidates will have practical experience incorporating Gen AI tools into their analytical workflows. They demonstrate strong ownership of requirements, support testing and validation activities, and can facilitate discovery sessions that result in timely, structured documentation and actionable outcomes. Experience in a client-facing or professional services environment is a meaningful advantage.