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Plotly builds the tools millions of developers use to work with data. Dash is one of the most popular ways to build data applications in Python, and the company is integrating AI features across its stack. Dash Enterprise is the commercial platform that lets organizations deploy, scale, secure, and govern data applications inside their own Kubernetes clusters, on-prem or in private cloud.
This is a hands-on Senior or Staff Engineer position focused on building product components end-to-end, from design through production. You will own features and take real, end-to-end responsibility for components you work on. The role involves solving hard problems in distributed systems, reliability, and operability in environments the company does not directly control—customers run the platform inside their own Kubernetes clusters.
Key responsibilities include:
- Designing, architecting, and implementing product features end-to-end
- Building and maintaining integrations that let the platform integrate natively with customer infrastructure and services
- Instrumenting the platform with observability (tracing, metrics, logging) and turning telemetry from customer deployments into product improvements
- Constructing software that installs, upgrades, and runs reliably inside customers' own Kubernetes clusters
- Strengthening platform reliability and availability for large, restricted customers
- Collaborating with product and technical leads on what to build and how
- Mentoring and raising the bar across the engineering team
Plotly is a heavy adopter of the latest AI coding tools and encourages engineers to experiment with new tools and processes while maintaining engineering rigor and quality.
Requirements:
- Proven production experience: you have designed and managed large production systems and understand what it takes to build and maintain them properly
- Deep fundamentals and range: comfortable applying expertise from one domain to unfamiliar problems rather than being narrowly specialized
- Platform expertise: experience with Kubernetes, distributed systems, and microservice orchestration
- Hands-on distributed systems debugging: tracing, metrics, performance analysis, and observability
- Networking knowledge: familiarity with how networking behaves inside Kubernetes
- Security fundamentals: experience resolving vulnerabilities and CVEs, using scanners and tooling to manage them
- Strong application-level engineering: solid system design principles, experience building user-facing production applications for enterprise customers, fluency in two or three programming languages (primarily Go and TypeScript)
- Self-managed/on-prem experience: shipped enterprise software that runs in environments you don't operate
- Hands-on builder: want deep technical impact and to stay hands-on
Nice-to-haves:
- Experience with hosting platforms, PaaS, or internal developer platforms (especially running arbitrary or untrusted user code safely)
- Temporal or another durable-workflow engine
- Identity and SSO integration experience
- Container build systems
- Integrating AI/LLMs into production and enterprise systems
- Python or Dash ecosystem experience
