Company Description

We are Software Mind, an awesome team of engineers who are ready to ramp up any top-notch company’s projects! Our aim? To always be one step ahead. Become part of a multicultural company in constant growth with an excellent work environment certified by Great Place To Work!

Job Description

About the Project Software Mind is building a private, tenant-isolated AI assistant for the real estate title and settlement industry. The platform is a retrieval-first (RAG) system that ingests historical email, documents, and structured metadata into a per-tenant vector index, and serves grounded, cited, expert-weighted answers through a chat-style Q&A interface with single sign-on and full audit logging. The platform is AWS-native with a Python/FastAPI backend, Vue.js frontend, OpenSearch/Pinecone vector store, and OpenAI/Anthropic/Bedrock as LLM provider. You will join a senior, cross-functional LATAM-based team where hands-on AI delivery experience not just familiarity is the baseline expectation. You will serve as the requirements and alignment anchor for the engagement translating domain knowledge, SME expertise patterns, and retrieval accuracy logic into structured, traceable specifications the engineering team can build against. You will also design the accuracy validation rubrics used at go/no-go gates. This is not a documentation-only role. Your Responsibilities 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 Tech Stack: Jira, Confluence, Microsoft 365, Miro, FigJam.

Qualifications

Must-Have Skills & Experience 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 Additional Information

Nice-to-Have

Domain exposure to legal, compliance, financial services, or document-heavy regulated industries Experience with PII classification, data governance, or privacy-by-design requirements Familiarity with LangChain, vector search concepts, or document processing pipelines at a conceptual level We are accepting applications from LATAM countries