[VCK] Senior Development Lead (AI +RAG Platform )
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 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 +90% English written and oral (at least B2 level) with excellent communication skills 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