GenAI Opportunity Scout & AI Business Analyst

RADcube - A NLogix Company; Indianapolis (IN); On-site; USD 90,000 - 120,000; Full time

Job summary

RADcube - A NLogix Company seeks an AI Business Analyst onsite in Indiana to partner with business units, identify AI, GenAI and data opportunities, and lead discovery workshops. You will translate challenges into AI use cases, define requirements, user stories, acceptance criteria, and KPIs, aligning data needs with engineering teams.

The ideal candidate is proactive, consultative, and capable of shaping the business value of AI initiatives through measurable outcomes and effective UAT planning.

Qualifications

• Strong understanding of AI and GenAI fundamentals, including LLM and RAG concepts.
• Proven experience leading discovery sessions and workshops with business stakeholders.
• Hands-on experience writing requirements, user stories, acceptance criteria and UAT plans.
• Ability to define KPIs and articulate business value for AI initiatives.
• Proactive and consultative approach with strong communication skills.

Responsibilities

• Partner with business units to identify high value AI, GenAI and Data opportunities
• Lead stakeholder discovery, workshops, process mapping and current and future state analysis
• Translate business challenges into AI use cases, requirements, user stories and acceptance criteria
• Define KPIs, expected business value, UAT requirements and implementation priorities
• Work with data and engineering teams to align use cases with data requirements
• Help grow the engagement by identifying new AI and Data workstreams

Skills

AI fundamentals

GenAI concepts

Discovery workshops

Requirements writing

KPIs & value

Tools

Databricks

NVIDIA platforms

Job description

RADcube - A NLogix Company seeks an AI Business Analyst onsite in Indiana to partner with business units, identify AI, GenAI and data opportunities, and lead discovery workshops. You will translate challenges into AI use cases, define requirements, user stories, acceptance criteria, and KPIs, aligning data needs with engineering teams.

The ideal candidate is proactive, consultative, and capable of shaping the business value of AI initiatives through measurable outcomes and effective UAT planning.