Principal Engineer, App Platform

Atlan is building the context layer for enterprise AI. Enterprises are pouring money into AI, but most of it fails in production because the AI lacks understanding of the business context around the data. Atlan solves this problem.

Gartner has identified context as the defining issue in enterprise AI and calls context graphs the essential infrastructure for AI agents, naming Atlan one of three vendors already building it. Atlan is also the only vendor named a Leader across all four major Gartner and Forrester evaluations for data catalogs, data governance, and metadata management—the foundation for the context layer.

Come build the infrastructure that AI runs on.

The Team

Atlan is executing a strategic shift: “In the future of Atlan, everything is an App.” The App Platform team is central to this transformation, building the core platform that enables teams to build, run, distribute, and scale Apps across Atlan.

The team owns key platform capabilities including SDKs & APIs, App Runtime, Distribution, Lifecycle, Automation, and Agent Platform infrastructure.

As Atlan transitions from Metadata → Context, Data Governance → Agentic Outcomes, and Product → Apps, the App Platform is becoming increasingly central to how we build the product. We’re looking for engineers who can own complex technical domains end-to-end, build reliable systems at enterprise scale, and help shape Atlan’s AI-native engineering practices.

What You’ll Do

• Define and drive the architecture and technical strategy for Atlan's App Platform.

• Design and build foundational platform primitives that enable apps to be developed, distributed, and executed at scale.

• Solve complex distributed systems challenges, including multi-tenancy, workload isolation, tenant-aware scaling, fault tolerance, and observability.

• Lead high-impact initiatives end-to-end, from problem discovery and RFCs to implementation, rollout, and long-term ownership.

• Build and evolve cloud-native infrastructure on Kubernetes across AWS and GCP.

• Drive architectural alignment across App Runtime, Distribution, Builder Experience, Product, and Infrastructure teams.

• Influence technical direction across teams through design reviews, mentorship, and engineering best practices.

• Remain hands-on in solving complex technical problems and validating critical architectural decisions.

• Leverage AI-assisted development tools such as Claude and Cursor to improve engineering velocity and quality.

• Contribute to long-term platform strategy, architectural documentation, and RFCs.

What Makes You a Match

• 14+ years of experience building and operating large-scale backend, infrastructure, or platform systems, with experience operating at a Principal Engineer level or equivalent.

• Deep expertise in distributed systems, Kubernetes, containerization, and cloud-native architectures.

• Strong hands-on experience with AWS, GCP, or Azure, including networking, compute, storage, and security.

• Proven experience designing and operating highly available, fault-tolerant, and mission-critical systems at scale.

• Strong understanding of platform engineering principles, including reliability, automation, self-service, and developer experience.

• Experience designing multi-tenant systems with deep observability and operational excellence.

• Demonstrated ability to define architecture, drive technical strategy, and influence decisions across multiple engineering teams.

• Strong technical judgment and the ability to balance long-term investments with pragmatic execution.

AI-Native Mindset

• You design platforms for non-deterministic workloads and AI-powered applications.

• You think in terms of automation, leverage, and feedback loops.

• You’ve supported or built infrastructure for AI/ML or AI-powered systems.

• You actively leverage AI in your own development workflow to improve speed, quality, and engineering leverage.

• You help establish AI-native engineering practices across teams.

Principal-Level Expectations

• Ability to own ambiguous, high-impact problem spaces and drive clarity, architecture, and execution.

• Ability to influence technical direction across organizational boundaries without relying on formal authority.

• Strong communication skills and the ability to partner with senior engineers and engineering leadership.

• Willingness to remain hands-on while driving technical direction and creating leverage across the organization.