Job 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!

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 are the technical delivery lead the bridge between architectural intent and day-to-day engineering execution. You own code quality, technical decisions within the team, and the delivery of the core AI Extraction Gateway (Simple and Complex RAG). You are hands-on: coding, reviewing, and unblocking across the Python backend and retrieval layers.

Your Responsibilities

• Lead hands-on development of the AI Extraction Gateway, progressing from Simple RAG to Complex RAG

• Implement and tune the expert-weighted (SME) retrieval layer and structured result validation

• Own confidence score calibration; collaborate with the BA on accuracy rubrics and test evidence

• Drive technical delivery cadence: sprint planning, code reviews, technical risk identification, and team unblocking

• Ensure architectural patterns are implemented consistently across the codebase

• Collaborate with the Data Engineer on ingestion pipeline integration points and vector store schema

• Implement and evolve the query orchestration layer (Python/FastAPI, AWS Lambda/ECS)

• Support the QA Automation Engineer in designing the validation harness for RAG outputs

• Maintain development observability: structured logging, CloudWatch dashboards, X-Ray tracing

• Tech Stack: Python, FastAPI, AWS (ECS, Lambda), OpenSearch, Pinecone, OpenAI, Anthropic, Bedrock, DynamoDB, S3, CloudWatch, X-Ray, Docker, Jira, Confluence.

Must-Have Skills & Experience

• 6+ years in software development; minimum 2 years in a tech lead or senior engineering lead capacity

• Strong Python development skills; FastAPI or equivalent async Python framework required

• Hands-on AWS experience: ECS and/or Lambda, API Gateway, DynamoDB, S3, CloudWatch, X-Ray

• Experience with vector databases OpenSearch, Pinecone, Weaviate, or equivalent

• Solid understanding of API design, service decomposition, and clean backend architecture

AI Experience (Required Not Optional)

• Delivered at least one production RAG, semantic search, or LLM-integrated application end-to-end not a prototype or internal tool

• Practical experience integrating with LLM provider APIs (OpenAI, Anthropic, or Amazon Bedrock) in a production or enterprise configuration

• Working knowledge of chunking strategies, embedding models, retrieval ranking, and prompt engineering in a production context

• Experience with confidence scoring, retrieval evaluation, or hallucination mitigation approaches in a deployed system

Qualifications

Nice-to-Have

• Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks

• Familiarity with OCR pipelines and document extraction tooling (AWS Textract, Tesseract, or equivalent)

• Exposure to multi-tenant data isolation patterns and tenant-scoped encryption key management

We are accepting applications from LATAM countries

Additional Information