Senior AI/Data Engineer - Cotton Holdings Inc.

AI & Data Platform Engineer

Location: Houston, TX (Hybrid Preferred) or Remote (U.S./LATAM) Type: Contract-to-Hire Level: Mid-Senior

About the Role

We're hiring an AI & Data Platform Engineer to build AI-powered systems that automate RFP discovery, document analysis, and qualification workflows.

You'll work on backend AI systems that ingest RFPs, extract key information from documents, build semantic search, and help teams decide which opportunities to pursue.

This is a hands-on engineering role focused on production systems — not just prompt engineering.

What You'll Do

• Build AI workflows for RFP intake, document parsing, extraction, and qualification
• Create RAG and semantic search pipelines over RFP documents
• Extract structured data like due dates, project scope, contacts, requirements, and submission instructions
• Develop FastAPI services and backend APIs
• Build human review and approval workflows
• Improve reliability, testing, observability, and AI quality

Tech Stack

• Python
• FastAPI
• Pydantic / Pydantic AI
• PostgreSQL + pgvector
• SQLAlchemy
• Azure OpenAI
• Azure Blob Storage
• Prefect
• Docker
• GitHub

Requirements

• 4+ years of software engineering experience
• 2+ years building backend APIs or data platforms in production
• Strong Python backend engineering experience
• Experience with LLMs, RAG, embeddings, or AI workflow automation
• Experience with PostgreSQL and relational databases
• Strong understanding of data modeling and validation
• Ability to build clean, reliable, maintainable systems

Nice to Have

• LangChain, LangGraph, LlamaIndex, or similar frameworks
• OCR, PDF parsing, or document intelligence experience
• Azure AI services experience
• Vector database or pgvector experience
• Prefect, Airflow, or orchestration tools
• Experience with construction, procurement, legal, or document-heavy workflows

Ideal Candidate

You're a pragmatic engineer who understands that production AI requires more than prompts. You know how to build scalable systems with strong validation, clean architecture, and reliable workflows.