Senior Business Analyst – AI Platform

This is a fully remote position, open to applicants in Argentina.

📋 Description

• Lead sessions for discovery and workshops aligning with Subject Matter Experts (SMEs); create organized documentation for requirements and integration assumptions.

• Specify the scope for data ingestion, including folder selection, corpus boundaries, PII classification needs, and tenant governance guidelines.

• Convert expert-weighted business logic into detailed specifications for the retrieval and ranking processes.

• Create and uphold the accuracy rubric framework utilized for SME validation.

• Develop and authenticate user stories that comply with the INVEST criteria, ensuring acceptance criteria are linked to delivery milestones.

• Generate and sustain schema documentation for the data processing pipeline.

• Conduct query clustering analysis to prioritize efforts in accuracy tuning.

• Act as a liaison between the input from client Designated Experts and the engineering team's implementation backlog.

• Ensure requirements traceability across Jira and Confluence throughout all project phases.

⛳️ Requirements

• Over 6 years of experience as a Business Analyst on software delivery projects; a senior level of expertise is required.

• Demonstrated skill in converting complex business requirements into structured, developer-ready specifications (user stories, use cases, acceptance criteria).

• Strong data literacy, with the capability to understand document structures, metadata schemas, and classification logic.

• Experience in gathering requirements from domain SMEs and translating them into actionable specifications.

• Expertise in authoring user stories, managing backlogs, and defining acceptance criteria in agile settings.

• Exceptional written and verbal English communication skills; direct engagement with client stakeholders is anticipated.

• AI experience is essential; involvement in at least one project that includes requirements definition or evaluation design for a production AI/ML or NLP system.

• Familiarity with RAG, search, classification, recommendation, or similar fields.

• Capability to define evaluation criteria and accuracy rubrics for AI system outputs, extending beyond mere functional requirements.

• Conceptual understanding of LLM behavior, grounding, hallucination risk, and retrieval relevance trade-offs, sufficient to formulate testable acceptance criteria.

• Experience serving as a bridge between domain subject-matter experts and AI/ML engineering teams.

🏝️ Benefits

• Employees have the option to work remotely.