Software Engineer (Back-end)
WFA Digital Insight
TensorWave’s platform team is looking for a senior back‑end engineer who will own the full lifecycle of massive GPU clusters. The role isn’t just about writing Go code; it requires stitching together bare‑metal provisioning, Kubernetes operator development, and Slurm automation into repeatable pipelines. Candidates will be hands‑on with hardware‑level concepts like PXE boot and BMC management while also delivering production‑grade gRPC and REST APIs. The position sits at the intersection of infrastructure reliability and rapid AI innovation, meaning the engineer’s work directly impacts how quickly developers can spin up compute resources. Expect close collaboration with cross‑functional partners and responsibility for observability stacks that keep the platform transparent and stable.
Job Description
About TensorWave
Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.
About the role
We’re looking for a Software Engineer (Back-end) to join our platform team during an exciting phase of growth. In this role, you’ll own the end-to-end automation of provisioning, configuring, and operating large-scale GPU clusters across bare metal, Kubernetes, and Slurm environments. This is a hands-on technical role focused on building the tooling and pipelines that bring hundreds of GPU nodes online reliably and repeatably—working closely with cross-functional partners to support business objectives while upholding our standards for excellence, collaboration, and impact.
Responsibilities
Build and maintain fully automated pipelines for provisioning bare metal GPU clusters from zero to production
Automate Slurm and Kubernetes cluster lifecycle—bootstrapping, upgrades, node provisioning, and decommissioning at scale
Develop and maintain infrastructure for GPU node configuration, including drivers and firmware
Own cluster validation pipelines, automating health checks and GPU burn-in tests
Build day-2 operations automation, including node remediation, rolling upgrades, and automated drain/cordon workflows
Write and maintain runbooks and documentation to enable reliable, repeatable operations
Own the full observability stack for automation services, provisioning pipelines, and cluster health systems
Required Experience
5+ years in infrastructure engineering or platform engineering
3+ years writing production Go
Deep understanding of Kubernetes internals, including:
Informers and work queues
Controller-runtime and client-go
CRDs, custom controllers, and operators
Admission webhooks
Experience building Kubernetes Operators
Experience building gRPC and REST APIs in Go at production scale
Familiarity with bare metal infrastructure concepts, including PXE, IPMI, and BMC
Strong testing discipline across unit, integration, and end-to-end tests
Proven ownership of observability stacks such as Prometheus, Grafana, OpenTelemetry, and Loki (or similar)
Preferred Qualifications
Knowledge of GPU workload infrastructure
Experience with RoCE networking automation
Experience with GitOps tools such as ArgoCD
Experience with CI/CD tools such as GitHub Actions and Argo Workflows
Experience with Ansible and Terraform
What We Offer
Stock Options
100% paid Medical, Dental, and Vision insurance for Employees
Company Health Savings Account Contributions
100% paid Short Term and Long Term Disability Insurance for Employees
Life and Voluntary Supplemental Insurance Options
Other Insurance Options, such as Pet & Legal Insurance
Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support
Flexible Spending Account
401(k)
Employee Assistance Program
Flexible PTO
Paid Holidays
Parental Leave
Other In-Office Perks
Equal Employment Opportunity
TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.
Reasonable Accommodations
TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact accomodations@tensorwave.com.
Employment Eligibility
All offers of employment are contingent upon verification of identity and authorization to work in the United States, as required by law.
Background Checks
Where permitted by law, employment may be contingent upon the successful completion of a job-related background check.
Data Privacy Notice
By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.
How to Stand Out
- Highlight any production Go projects on your résumé, especially those involving gRPC or REST APIs.
- Demonstrate familiarity with Kubernetes operators by sharing code samples or open‑source contributions.
- Prepare to discuss concrete examples of automated bare‑metal provisioning or GPU driver management you have built.
- Include metrics or outcomes (e.g., reduced provisioning time, increased cluster uptime) in your interview stories.
- Review TensorWave’s tech stack and be ready to propose improvements to their observability pipeline.
- Ask about the team’s on‑call rotation and day‑2 automation responsibilities to gauge workload expectations.
- Negotiate equity by researching typical stock‑option grants for senior engineers in remote AI infrastructure firms.
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