Principal Software Engineer - Platform

Atlan; United States; Remote; USD 180,000 - 250,000; Full time

Job summary

Atlan is seeking a Principal Engineer to architect and scale the foundational data plane for the AI era. You will govern platforms handling billions of assets and 100K+ users with 99.99% availability. This high-autonomy role will set technical direction, drive multi-quarter initiatives, and push AI-native development practices.

You will design platform services, manage lakehouse and vector/graph infrastructures, and mentor engineers while shaping standards and RFCs across teams.

Qualifications

• 10+ years in platform engineering, infrastructure, or backend systems at a SaaS company.
• Experience building enterprise-scale distributed systems at scale.
• Deep expertise in multi-tenant architectures and tenant isolation strategies.
• Strong Kubernetes, containerization, and cloud infrastructure skills (AWS/GCP/Azure).
• Hands-on experience with distributed systems patterns - service mesh, event-driven architecture, orchestration.
• Track record of driving multi-quarter technical initiatives from concept through production at scale.

Responsibilities

• Design and build platform services - APIs, infrastructure components, runtime systems, and ingestion frameworks at enterprise scale.
• Architect the context store that transforms lakehouse infrastructure into AI-ready systems with multimodal capabilities (structured, unstructured, vector, graph).
• Solve complex multi-tenant isolation and scaling problems for enterprise SaaS.
• Design data contracts governing ingestion, validation, processing, routing, storage, and serving across heterogeneous systems.
• Own critical shared infrastructure including lakehouse (Iceberg/Polaris), vector stores, graph databases, and OLTP systems.
• Drive technical standards through RFCs, architecture reviews, and documentation.
• Mentor senior engineers and influence architecture decisions across teams.
• Write production code using AI-assisted development tools (Claude Code, Cursor).
• Debug distributed systems issues across Kubernetes, workflow orchestration, and microservices.

Skills

Platform engineering

Distributed systems

Multi-tenant architectures

Kubernetes & cloud (AWS/GCP/Azure)

Service mesh & event-driven design

Production-scale initiatives

Tools

Iceberg/Polaris lakehouse

Vector stores

Graph databases

OLTP systems

Job description

Who We Are

Most companies are racing to deploy AI, but very few have the foundation to make it work reliably. Atlan is building that missing layer: the context layer for enterprise AI. We connect the business context behind data so humans and agents can operate with far more accuracy and confidence. With backing from world-class investors including GIC, Insight Partners, Meritech, Peak XV, and Salesforce Ventures, we've earned the trust of most AI-forward enterprises like General Motors, Nasdaq, Workday and Elastic. Come build the infrastructure that AI runs on.

About the Role

Atlan is building the context layer for AI agents and applications - transforming how data platforms power the next generation of AI. We're looking for a Principal Engineer to help architect and scale the foundational data plane that makes it easy to build apps, agents, and solutions for the AI era. You'll work on systems handling billions of assets, serving 100K+ users, with 99.99% availability targets. This is a high-agency role where you'll define technical direction, drive multi-quarter initiatives, and pioneer AI-native development practices.

What you will do

• Design and build platform services - APIs, infrastructure components, runtime systems, and ingestion frameworks at enterprise scale
• Architect the context store that transforms lakehouse infrastructure into AI-ready systems with multimodal capabilities (structured, unstructured, vector, graph)
• Solve complex multi-tenant isolation and scaling problems for enterprise SaaS
• Design data contracts governing ingestion, validation, processing, routing, storage, and serving across heterogeneous systems
• Own critical shared infrastructure including lakehouse (Iceberg/Polaris), vector stores, graph databases, and OLTP systems
• Drive technical standards through RFCs, architecture reviews, and documentation
• Mentor senior engineers and influence architecture decisions across teams
• Write production code using AI-assisted development tools (Claude Code, Cursor)
• Debug distributed systems issues across Kubernetes, workflow orchestration, and microservices

What makes you a match?

Must Have

• 10+ years in platform engineering, infrastructure, or backend systems at a SaaS company
• Experience building enterprise-scale distributed systems at scale
• Deep expertise in multi-tenant architectures and tenant isolation strategies
• Strong Kubernetes, containerization, and cloud infrastructure skills (AWS/GCP/Azure)
• Hands-on experience with distributed systems patterns - service mesh, event-driven architecture, orchestration
• Track record of driving multi-quarter technical initiatives from concept through production at scale

Strong to Have

• Experience designing contract-driven or schema-first data platforms
• Familiarity with Temporal or similar workflow orchestration systems
• Data quality frameworks, observability systems, and cost attribution at scale
• Experience supporting enterprise workloads with strict compliance requirements
• CI/CD pipeline design and GitOps practices

Who You