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Senior Business Analyst – AI Platform
Software MindSenior Business Analyst at Software Mind working on a tenant-isolated AI assistant for real estate. Collaborating with a senior LATAM-based team to translate requirements and validate accuracy.
About the role
Key responsibilities & impact- Lead discovery sessions and SME alignment workshops; produce structured requirements and integration assumption documentation
- Define data ingestion scope: folder selection, corpus boundaries, PII classification requirements, and tenant governance rules
- Translate expert-weighting business logic into specifications for the retrieval and ranking layer
- Author and maintain the accuracy rubric framework used for SME validation
- Write and validate user stories (INVEST-compliant) with acceptance criteria tied to delivery milestones
- Produce and maintain schema documentation for the data processing pipeline
- Facilitate query clustering analysis to prioritise accuracy tuning work
- Bridge between client Designated Expert input and the engineering team's implementation backlog
- Maintain requirements traceability across Jira and Confluence throughout all phases
Requirements
What you’ll need- 6+ years as a Business Analyst on software delivery projects; senior seniority required
- Proven ability to translate complex business needs into structured, developer-ready requirements (user stories, use cases, acceptance criteria)
- Strong data literacy: ability to reason about document structures, metadata schemas, and classification logic
- Experience eliciting requirements from domain SMEs and translating them into implementable specifications
- Proficiency with user story authoring, backlog management, and acceptance criteria definition in agile environments
- Excellent written and spoken English direct engagement with client stakeholders is expected
- AI Experience (Required Not Optional) At least one project involving requirements definition or evaluation design for a production AI/ML or NLP system RAG, search, classification, recommendation, or similar
- Ability to define evaluation criteria and accuracy rubrics for AI system outputs not just functional requirements
- Understanding of LLM behaviour, grounding, hallucination risk, and retrieval relevance trade-offs at a conceptual level sufficient to write testable acceptance criteria
- Experience bridging between domain subject-matter experts and AI/ML engineering teams
Benefits
Comp & perks- Excellent work environment certified by Great Place To Work!
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
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Hard Skills & Tools
data ingestionPII classificationuser story authoringacceptance criteria definitionschema documentationquery clustering analysisrequirements traceabilityAI/ML system evaluationmetadata schemasclassification logic
Soft Skills
communicationstakeholder engagementcollaborationanalytical thinkingproblem-solvingorganizational skillsattention to detailfacilitationtranslating complex needswriting skills