Principal Architect – Platform, Data Lake

TetraScience

Principal Architect responsible for platform architecture and scaling for scientific data and AI in biopharma at TetraScience. Drive technical direction and oversee enterprise-grade capabilities in a rapidly growing environment.

Posted 7/15/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in platform architecture and operational excellence, with a strong focus on AI/ML infrastructure, enterprise authentication systems, and data lake architectures. Proven ability to lead cross-team initiatives and communicate complex architectural decisions effectively.

Highest-signal resume keywords

Platform Architecture OwnershipAI/ML Serving InfrastructureEnterprise Authentication SystemsData Lake ArchitecturesAWS Infrastructure Fluency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringArchitecture DesignModel Inference PipelinesSearch Platform DesignDelta LakeApache IcebergSAMLOIDCRBACKubernetes

Soft Skills

Cross-Team CommunicationDocument Writing

Tools & Technologies

AWSECS

Industry Keywords

SaaSData InfrastructureOperational ExcellenceMulti-TenantSchema EvolutionQuery PerformanceStorage Cost

Tech Stack

Tools & technologies

ApacheAWSCloudKubernetes

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Comp & perks

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