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TetraScience

Open | Cloud-Native | Purpose-Built for Science

Principal Architect – Platform, Data Lake

Backend EngineerSoftware EngineerFull TimeRemoteLeadTeam 51-200Since 2015H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

13 hours ago

Salary

0

Seniority

Lead

Postgraduate Degree12 yrs expEnglishApacheAWSCloudKubernetes

Job Description

Principal Architect – Platform, Data Lake

TetraScience

• Own the platform architecture, evolution and growth scaling across Enterprise Platform, Scientific Search, AI/ML Ops, Developer Platform, Developer Productivity, Lakehouse Platform, Partner Integrations and Cloud Infrastructure. • Set technical direction, own the decisions that cross team boundaries, and close architectural gaps before they become business risks. • Oversee enterprise Platform, Scientific Search, AI/ML Ops, Developer productivity, Lakehouse platform, and Cloud Infrastructure. • Ensure operational excellence based on a clear O11y architecture rolled out, with every production service having SLOs defined, monitored and managed. • Achieve strong product-market fit and traction while expanding industry partnerships and developer experience.

Job Requirements

  • 12+ years in software engineering, with at least 5 at staff or principal level in a SaaS platform or data infrastructure context.
  • Deep architecture ownership in at least one of the two fingerprint profiles above, with meaningful range across the other. Coverage of a majority of the eight domains is the bar.
  • Demonstrated ownership of enterprise authentication and authorization systems at scale: SAML, OIDC, fine-grained RBAC across a multi-tenant SaaS product. You have been the person who got paged when auth broke, not just the person who designed it.
  • Hands-on experience with AI/ML serving infrastructure: you have built and operated model inference pipelines under production load.
  • Search architecture experience: you have designed and operated a search platform that handles diverse query types (keyword, semantic, or hybrid) across large structured or semi-structured datasets.
  • Hands-on experience with data lake architectures at scale: Delta Lake or Apache Iceberg, schema evolution patterns, partition pruning, and the trade-offs between query performance and storage cost.
  • Infrastructure fluency on AWS with Kubernetes or ECS. You can read a cost anomaly report, trace it to a root cause, and produce an action within the same week.
  • Ability to write and defend architecture decisions: RFCs, trade-off documents, design reviews.
  • Strong cross-team communication. You can write a document that produces alignment without a follow-up meeting to explain the document.
  • Comfort operating across strategy, architecture, and operations in the same week: setting a multi-year architecture direction and reviewing a runbook gap are both in scope.

Benefits

  • Competitive compensation with equity
  • Unlimited PTO
  • Company-paid Life Insurance, LTD/STD
  • 401(k)

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