AI Compliance Platform Co-Lead
Budget: $25 – $50 USD
From February 1 through March 27 I need an experienced engineer to work side-by-side with me as both system architect and AI/data co-lead on a new platform that streamlines regulatory compliance for construction and engineering firms.
Your first hat is architecture: own the technical roadmap, design a secure, cloud-native stack, and lay out the integrations that keep every microservice traceable and explainable. The hosting provider is still open—AWS, Google Cloud Platform, or Microsoft Azure—so you’ll guide the final choice based on scalability, cost, and our security model.
Your second hat is AI & data engineering:
• Build and fine-tune NLP pipelines that can read specs, permits, and inspection reports.
• Design and populate a knowledge graph that maps OSHA, ISO, local building codes, and all NJ state building and construction regulations.
• Add generative components that surface plain-language explanations and remediation steps.
• Set up data ingestion, normalization, version control, and continuous evaluation so models remain trustworthy.
Key outcomes by March 27
• Complete architecture diagrams and a living technical roadmap.
• Deployed prototype with working NLP + knowledge graph services behind a simple API.
• Monitoring dashboards that report accuracy, drift, and security posture.
If you are fluent in cloud architecture, knowledge graphs, responsible AI, and large-scale integrations, let’s talk specifics and lock in the timeline.
Your first hat is architecture: own the technical roadmap, design a secure, cloud-native stack, and lay out the integrations that keep every microservice traceable and explainable. The hosting provider is still open—AWS, Google Cloud Platform, or Microsoft Azure—so you’ll guide the final choice based on scalability, cost, and our security model.
Your second hat is AI & data engineering:
• Build and fine-tune NLP pipelines that can read specs, permits, and inspection reports.
• Design and populate a knowledge graph that maps OSHA, ISO, local building codes, and all NJ state building and construction regulations.
• Add generative components that surface plain-language explanations and remediation steps.
• Set up data ingestion, normalization, version control, and continuous evaluation so models remain trustworthy.
Key outcomes by March 27
• Complete architecture diagrams and a living technical roadmap.
• Deployed prototype with working NLP + knowledge graph services behind a simple API.
• Monitoring dashboards that report accuracy, drift, and security posture.
If you are fluent in cloud architecture, knowledge graphs, responsible AI, and large-scale integrations, let’s talk specifics and lock in the timeline.