Platform Architect
US$200,000 – US$270,000 / yr base salary
Posted 15 Jul 2026
Advertised as “Principal Platform Architect”
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
| Base salary | US$200,000 – US$270,000 / yr |
|---|
The role
TetraScience is building TetraOS - the category defining Scientific OS for biopharma. The Tetra Platform is the foundation for developing, delivering and operating our enterprise grade, secure, compliant Scientific Data and AI capabilities customers build upon. After achieving strong product-market fit and traction, TetraScience is entering a growth scaling phase where we are expanding our industry partnerships and developer experience to rapidly build the foundations of AI-native scientific data and workflows in production.
In this role, you will own the Tetra Platform architecture, its evolution, and the partner integrations that extend it. This is an IC leadership role. You will define the platform architecture aligned with the product and business strategy. You will inform roadmap alignment decisions and trade-offs.
The scope of this role is intentionally broad. We are looking for experienced candidates who have gone deep in two to three technology domains to gain breadth and depth of architectural, execution and operational experience. Your experience spans startups and large companies, so you understand the trade-offs at different stages and scales. Strong candidates will have deep, diverse experience with operational excellence and agility in building in a dynamic business context.
The Tetra Platform spans the following diverse technology domains:
- Enterprise Data & Agentic AI Platform: Multi-tenant cloud architecture, Durable workflows, AWS, Databricks, RBAC/ABAC, IAM, observability and infrastructure chargebacks.
- Data, Knowledge, and Developer Products: Search, Semantic layer foundations, knowledge and ontology layers and products, external developer platforms.
What you’ll own:
- Enterprise Platform: Tenancy, IAM, Compliance and control plane that enterprise customers use to govern their scientific data environment: SSO/SAML/OIDC, fine-grained RBAC / ABAC for SQL access.
- Scientific Search: Search architecture spanning keyword, semantic, and hybrid retrieval across scientific data, instruments, and metadata: relevance standards, indexing pipeline, and the infrastructure that makes search a reliable product surface.
- AI / ML Ops: Model lifecycle, inference and training on platform, Agentic IAM and DX, telemetry, observability and frameworks that keep scientific AI outputs traceable and operable under production load.
- Developer Platform: External builder platform, low and high code scientific solution development experiences, golden path tooling for partner integrations, SDKs and adoption metrics.
- Developer Productivity: Developer throughput as a first-class metric: toolchain ownership, local/prod environment parity, and friction reduction from commit to deployment.