Render
Software Engineer, Compute Infrastructure
Remote: United States
Sponsorship not specifiedDetected 115 days ago
GoRustNode.jsFull-Stack DevelopmentCloud PlatformsKubernetesLinuxLLMsA/B TestingComplianceRecruitingEmbedded SystemsDNS
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odds of building a lasting career here
37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
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from this employer's Department of Labor filings
Files H-1B transfers
3 transfer filings in the last year, covering 3 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
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About the role
- Our customers have created millions of services on our platform, and the numbers continue to accelerate.
- We leverage open source and industry-standard technologies, modifying and extending the core components to meet the unique reliability, performance, and scaling demands of our platform.
- We are looking for engineers with deep specialization in cloud and compute infrastructure.
Responsibilities
- Own Render's core compute infrastructure across multiple cloud providers, regions, and data centers. You'll shape how we evolve our compute platform as we rapidly scale.
- Design and build capabilities that give users greater performance and flexibility in how their services are built, deployed, perform, and stay available even when underlying resources go down.
- Partner with engineers across the company to build a platform that is stable, predictable, and secure.
- Experience developing in Go, Rust, or similar languages to develop custom infrastructure components, scheduling, controllers, that apply business logic to resource management.
- Own Render's core compute infrastructure across multiple cloud providers, regions, and data centers.
- We will also work with you to create a supportive plan of return.
Requirements
- At least 7 years of experience building and operating large-scale platform or compute infrastructure.
- Deep expertise in operating, scaling, and enhancing Kubernetes clusters or similar resource/container orchestration system.
- Comfort going broad and deep in a complex systems, making tradeoffs to improve performance and efficiency without sacrificing reliability.
- Strong experience designing, debugging, and operating distributed systems.
- Experience planning and executing rapid, high-risk upgrades, changes with minimal downtime to user services.
- Experience optimizing the performance of node, pod, and container spin-up times.
- Familiarity with eBPF, Linux kernel internals, resource management.
- Comfort securing and isolating workloads in multi-tenant execution environments.
Benefits
- 4 weeks of paid vacation.
- 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child.
- Long-term disability, life insurance, and 401K plans.
- 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent.
- Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc.
- Continuous learning benefits & related support.
- Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders.
Company info
- Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms-so teams can ship fast, scale reliably, and focus on their product, not infrastructure.
- Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively.
- We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team.
Equal opportunity
- Please contact us to request accommodation.
Visa & Work Authorization
- This position is generally not eligible for new visa sponsorship.
This listing is sourced directly from Render's careers page and normalized into a canonical job model.