AI Platform Engineer

Our platforms turn messy source documents into numbers an investment committee or an accountant can defend. That only works if the AI layer is engineered like production software: measured, versioned, and traceable. You own that layer. You will design extraction and reconciliation pipelines, build the evaluation harnesses that decide whether a model change ships, and integrate the results into the .NET and React platforms our clients run every day. You work directly with the founder and the senior team; what you build goes to production with your name on it. What you'll own Document AI pipelines: extraction, validation, and reconciliation flows that turn source documents into structured, verified data. Traceability: every figure the platform produces links back to the document line it came from. You design and defend that guarantee. Evaluation: regression suites and accuracy benchmarks that gate every model or prompt change before it reaches production. Orchestration: model selection, prompt architecture, and cost and latency budgets across providers. Integration: AI services exposed cleanly to .NET Core back ends and React front ends. Operation: monitoring for drift and failure modes in live systems, and triaging what the monitors catch. Technical skillsLLM engineering: production experience with frontier model APIs (Anthropic, OpenAI, or Azure OpenAI), structured output, and retrieval.