Senior Full-Stack Developer AI SaaS MVP Build

We are building an AI-powered SaaS platform focused on structured document intelligence and audit-ready evaluations. This is not a chatbot or simple GPT wrapper. The platform is designed to analyze complex documents through a multi-step evaluation pipeline using deterministic scoring, structured outputs, and traceable findings. The architecture, data model, scoring approach, and core pipeline logic are already defined. We are looking for an experienced engineer or small team to implement the MVP from an existing system design. Core Platform Goals • Structured document analysis (PDF/Word) • Checklist-based evaluations • Deterministic scoring logic • Traceable and auditable outputs • Gap analysis and recommendations • Structured report generation • Multi-stage AI processing pipeline The initial use case focuses on technical and regulatory documents, but the platform is designed to support multiple industries over time. Current Status We already have: • System architecture and service boundaries • Defined AI pipeline design • Deterministic scoring model • Data models and core entities • MVP scope and modules This is an implementation-focused engagement, not a discovery phase. Scope of Work — MVP Core Features • Document upload (PDF/Word) • Parsing and document structuring • Chunking and checklist mapping • LLM-based evaluations with schema-constrained outputs • Validation and consistency checks • Deterministic scoring engine • Findings aggregation and gap analysis • Structured reporting Platform Requirements • Basic multi-tenant setup • API layer and backend services • Async processing using queues/workers • Document and structured data storage Technical Requirements Strong experience with: • Full-stack SaaS applications • AI/LLM integrations • Document processing pipelines • Async architecture and background workers • Scalable backend systems Preferred stack: • Python and/or Node.js • React • PostgreSQL • Object storage • API-driven architecture Important This is NOT: • A chatbot • A one-step AI tool • A prompt wrapper product We are building a structured evaluation platform where deterministic logic, reproducibility, and auditability matter. Engagement Details Looking for: • Fixed-price MVP build • Clear milestone breakdown • Timeline estimation • Cost estimation Please include: Similar SaaS or AI systems you have built Your approach to a system like this Estimated MVP timeline Estimated MVP budget range Whether you work solo or with a team Architecture Question We are building a multi-step AI evaluation system with: • structured document parsing • checklist-based evaluations • deterministic scoring outside the LLM • traceable outputs At a system level, how would you structure the backend architecture to support: • traceability between outputs and source evidence • deterministic scoring • re-runs when rules or evaluation criteria change Please explain your proposed services, pipeline structure, and data flow. Execution & MVP Planning Question For a platform that includes: • document upload • parsing and structuring • multi-step AI evaluation • checklist scoring • dashboards and reporting How would you break the MVP into phases? Please include: • estimated timeline • key milestones • what should be built first vs later AI Pipeline Question How would you design the AI evaluation pipeline so outputs remain: • schema-structured • consistent across runs • auditable • linked to source evidence Please explain how you would: • control LLM behavior • validate outputs • maintain consistency across evaluations Additional Notes Architecture documents and internal specifications will be shared after NDA. We are looking for experienced engineers who can build production-quality systems with long-term scalability in mind.