Chief Platform Engineer

A C‑suite technical leadership role owning the entire data layer beneath a next‑generation reasoning platform. This seat reports directly to the CTO and assumes full responsibility for the ontology, knowledge graph, pipelines, and platform‑layer direction. You’ll inherit a lean, high‑impact system, evolve it, and ultimately build and lead the platform engineering team.

Role Overview

You will design and maintain the core ontology in TypeDB/TypeQL, defining the entity types, relations, and rules that model scientific workflows — experiments, assays, materials, evidence. You’ll own the production knowledge graph and Qdrant vector store, driving schema evolution, query performance, and hybrid symbolic‑plus‑semantic retrieval.

You’ll architect ingestion and entity‑resolution pipelines that normalize heterogeneous, messy inputs (instrument data, ELN/LIMS, publications, assay results) with strict provenance at write time. You’ll define and enforce the audited write path to the symbolic layer — agents read but never mutate.

You will also lead platform security end‑to‑end: RBAC/ABAC, tenant isolation, secrets management, encryption, audit logging. You’ll drive SOC 2 readiness and prepare the platform for GxP and 21 CFR Part 11 compliance.

What You’ll Own

Ontology design in TypeDB/TypeQL
Knowledge graph + Qdrant vector store in production
Schema evolution, query performance, hybrid retrieval
Ingestion + entity‑resolution pipelines with provenance
Controlled, audited write path for symbolic data
Platform security: authN/authZ, isolation, secrets, encryption, audit trails
SOC 2 certification and regulated‑data readiness
SLOs, observability, and reliability across FastAPI services
Engineering standards and hiring the platform team

Ramp: Week 1 — deep dive into internal docs and data‑interaction patterns. By end of Month 1 — full ownership of platform development and evolution.

Requirements

Designed and operated production ontologies or knowledge models (e.g., semantic layers, master‑data systems, knowledge graphs)
Strong command of TypeDB/TypeQL, Neo4j, or RDF/SPARQL
Production‑grade Python backend; FastAPI or equivalent
Experience building pipelines against heterogeneous, messy data sources
Applied security experience: authorization models, multi‑tenant isolation, secrets, encryption, threat modelling
Strong across both front‑end and back‑end engineering

Execution & Ownership

Sets architecture and operates autonomously in an early‑stage environment
Product‑obsessed, with genuine leadership instincts
First‑principles thinker — not reliant on boilerplate or AI‑generated scaffolding

Background

Wide experience band: early‑career high‑trajectory engineers through seasoned operators
CS fundamentals and formal education are strong signals
End‑to‑end personal projects, original research, or open‑source contributions weighted heavily

Location & Visa

In‑person role in San Francisco
Sponsorship available (H‑1B/L‑1)

Nice‑to‑Have

Vector search / retrieval (Qdrant or equivalent)
Life sciences, biotech, or scientific‑computing exposure
SOC 2 or HIPAA experience
Agent orchestration or probabilistic programming (DSPy, Pyro)
Philosophy or formal‑logic interest
Hackathon wins, coding‑competition medals, or athletic background