Senior Founding AI Software Engineer

Role overview This is a founding-level engineering role at a venture-backed, AI-native seed-stage startup building an intelligence platform that simulates regulatory outcomes for therapeutics companies and their investors. The work spans the full stack, from document ingestion and retrieval to agents, evaluations, and infrastructure, and is being built in close collaboration with former regulatory reviewers. The role is remote within the U.S., reports into a small engineering team, and carries a viable path to Head of Engineering.

Responsibilities - Build the evaluation and benchmark pipeline: regression suites, precision and recall measurement against expert judgement, and gating prompt, model, and agent changes - Build ingestion and retrieval over long, complex regulatory documents (scanned PDFs, Word files, tables, slide decks), including parsing, structure-aware chunking, and hybrid search - Design and ship agent systems, runtimes, and tool integrations that operate reliably in production - Strengthen the product surface in React, TypeScript, Vite, Tailwind, and the Vercel AI SDK - Own backend and persistence work in Python, FastAPI, SQLAlchemy, PostgreSQL, and Alembic, including idempotent and observable data pipelines - Support AWS infrastructure built on ECS/Fargate, Terraform, GitHub Actions, and separate dev/prod environments, with a focus on tenant isolation, RBAC, encryption, and audit logging

Requirements - 5+ years building and operating production software, including owning the architecture of a production system - Hands-on experience building evaluations against expert judgement (golden datasets, precision/recall) and using them to decide what ships - Experience shipping LLM systems to production, such as retrieval over complex documents or agent workflows - Daily use of AI coding tools, with the judgement to catch errors in migrations, infrastructure changes, and data-access code - Strong Python and data engineering skills: schema design, zero-downtime migrations, reliable pipelines, and background jobs on a relational database - Experience running production systems on a major cloud with infrastructure as code, CI/CD, and separate dev/prod environments

Nice to have - Working directly with domain experts (clinicians, lawyers, scientists) to turn their judgement into requirements and test cases - Retrieval techniques such as hybrid search, reranking, parsing scanned PDFs and tables, or knowledge graphs like GraphRAG - Agent frameworks and runtimes such as LangGraph, MCP, or Claude Agent SDK, including sandboxed agent execution - Post-training or fine-tuning (SFT, preference tuning, LoRA) and judgement on when it outperforms prompt and retrieval work - Building secure multi-tenant systems, AWS (ECS, RDS, S3), and Terraform

Benefits and work setup - Market-standard compensation, equity, and a path toward Head of Engineering or beyond - Remote within the United States; no visa sponsorship currently offered - Interview process: 30-minute intro with the CEO/cofounder, a 40-minute technical interview with a short hands-on exercise, a short paid take-home (5-8 hours) with a walkthrough, and a final round with a former regulatory decision-maker; decision targeted within two weeks of final round