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Job DescriptionAbout 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
We are accepting applications from LATAM countries
#LI-DNI
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
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
#LI-DNI
Skills Required
- 6+ years as a Business Analyst on software delivery projects; senior seniority required
- Proven ability to translate complex business needs into developer-ready requirements (user stories, use cases, acceptance criteria)
- Strong data literacy: reason about document structures, metadata schemas, and classification logic
- Experience eliciting requirements from domain SMEs and translating into implementable specifications
- Proficiency with user story authoring, backlog management, and acceptance criteria definition in agile environments
- Excellent written and spoken English for direct client engagement
- 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
- Understanding of LLM behaviour, grounding, hallucination risk, and retrieval relevance trade-offs to write testable acceptance criteria
- Experience bridging between domain subject-matter experts and AI/ML engineering teams
- Maintain requirements traceability across Jira and Confluence
- Domain exposure to legal, compliance, financial services, or other 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
Software Mind Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Software Mind and has not been reviewed or approved by Software Mind.
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Fair & Transparent Compensation — Pay is considered competitive for core hiring markets, with “good salary” cited in multiple locales. Public salary snapshots provide a baseline that helps candidates assess offers and negotiations.
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Flexible Benefits — Remote or hybrid options are prominently highlighted, and a remote‑work program is publicly noted alongside positively cited work‑from‑home experiences. Flexibility around schedules and location is presented as part of the package.
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Wellbeing & Lifestyle Benefits — Private medical care, language classes, sports/fitness support, and learning initiatives are listed for several Central/Eastern European locations, with occasional workation perks promoted. These lifestyle‑oriented offerings complement base pay and can enhance perceived total rewards.
Software Mind Insights
What We Do
Software Mind is a global digital transformation partner with operations throughout Europe, the US and LATAM. Driven by tech and empowered by people, we provide companies with software engineers and autonomous, cross-functional development teams who manage software life cycles from ideation to release and beyond. For over 20 years we’ve been enriching organizations with the talent they need to boost scalability, drive dynamic growth and bring disruptive ideas to life. Our top-notch engineering teams combine ownership with leading technologies, including cloud, AI, data science and embedded software to accelerate digital transformations and boost software delivery. A culture, driven by trust, that embraces openness, craves more and acts with respect enables our experts to create evolutive solutions that support scale-ups, unicorns and enterprise-level companies around the world.







