Senior AI/Data Engineer - Cotton Holdings Inc.
G2i Inc. • Huston
Posted: May 19, 2026
Job Description
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.
Additional Content
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.