Fractional CTO for AI Contract Platform
Budget: $15 – $25 USD
I have an early-stage, AI-native contract management product whose defining feature is powerful contract analysis driven by Natural Language Processing and automated data extraction. The proof of concept works; now I need a seasoned technical leader to turn it into a secure, scalable SaaS.
You will own the high-level architecture and guide a small engineering team so that every layer—from model serving to front-end delivery—can grow without drama. Cloud-agnostic design, container orchestration, CI/CD pipelines, microservices or modular monoliths: I’m open to whatever will give us low latency, predictable costs, and clean deployment workflows, provided we end up with true end-to-end encryption for all customer data, both at rest and in transit.
Key areas where I need your expertise
• Selecting and refining our NLP stack (e.g., spaCy, Hugging Face Transformers, RAG approaches) and the automated data-extraction pipeline.
• Designing a privacy-first data model that isolates tenant data, supports encrypted metadata search, and passes external pen-testing.
• Creating a scaling roadmap—load testing, horizontal/vertical autoscaling, cost observability, and graceful degradation strategies.
• Establishing DevSecOps culture: threat models, key management, audit logging, secret rotation, zero-trust access controls.
• Mentoring developers, enforcing code review standards, and signing off on each production release.
Initial deliverables
1. Architecture blueprint (system diagram, component rationale, tech stack choices).
2. Security specification covering encryption schemes, key lifecycle, compliance touchpoints.
3. 90-day engineering roadmap with milestones and resource estimates.
4. Review of current codebase with prioritized refactor list.
5. Weekly oversight sessions during implementation, culminating in the first customer-ready release.
If leading an AI product from prototype to robust, encrypted, cloud-scale service sounds like your idea of fun, let’s talk.
You will own the high-level architecture and guide a small engineering team so that every layer—from model serving to front-end delivery—can grow without drama. Cloud-agnostic design, container orchestration, CI/CD pipelines, microservices or modular monoliths: I’m open to whatever will give us low latency, predictable costs, and clean deployment workflows, provided we end up with true end-to-end encryption for all customer data, both at rest and in transit.
Key areas where I need your expertise
• Selecting and refining our NLP stack (e.g., spaCy, Hugging Face Transformers, RAG approaches) and the automated data-extraction pipeline.
• Designing a privacy-first data model that isolates tenant data, supports encrypted metadata search, and passes external pen-testing.
• Creating a scaling roadmap—load testing, horizontal/vertical autoscaling, cost observability, and graceful degradation strategies.
• Establishing DevSecOps culture: threat models, key management, audit logging, secret rotation, zero-trust access controls.
• Mentoring developers, enforcing code review standards, and signing off on each production release.
Initial deliverables
1. Architecture blueprint (system diagram, component rationale, tech stack choices).
2. Security specification covering encryption schemes, key lifecycle, compliance touchpoints.
3. 90-day engineering roadmap with milestones and resource estimates.
4. Review of current codebase with prioritized refactor list.
5. Weekly oversight sessions during implementation, culminating in the first customer-ready release.
If leading an AI product from prototype to robust, encrypted, cloud-scale service sounds like your idea of fun, let’s talk.