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 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 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
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
#LI-DNI
Skills Required
- 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
- 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
- Delivered at least one production RAG, semantic search, or LLM-integrated application end-to-end (not a prototype)
- Practical experience integrating with LLM provider APIs (OpenAI, Anthropic, or Amazon Bedrock) in production or enterprise configuration
- Working knowledge of chunking strategies, embedding models, retrieval ranking, and prompt engineering in production
- Experience with confidence scoring, retrieval evaluation, or hallucination mitigation approaches in a deployed system
- 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
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.
-
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.
-
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.
-
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.








