Software Engineer (Full Stack)
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
At TensorWave, we're revolutionizing AI computing by offering the most advanced cloud services, highlighted by our deployment of AMD Instinct Series GPUs. Our mission is to accelerate AI innovation by removing hardware limitations and ensuring scalable, efficient solutions for AI workloads. To support our rapid growth, we're seeking a Full Stack Engineer to join our team.
About The Role:
We are looking for a Full Stack Engineer to join our Product Engineering team. You'll build scalable, modern web applications and high-performance backend services that power TensorWave's next-generation AI cloud platform. Working directly with our cloud infrastructure team and UI/UX designers, you will lead the ground-up overhaul of our internal admin and customer-facing dashboards
This isn't a "close the ticket and move on" role. We're looking for problem solvers and owners who take full responsibility for what they build, dig into issues until they're truly solved, and consistently go above and beyond to deliver real value to our customers.
What You'll Do:
Lead the architecture and ground-up rebuild of our internal administrative tools and customer-facing dashboards.
Design and implement frontend applications using React.js and Next.js to provide seamless access to our GPU cloud services.
Develop robust APIs to support both multi-tenant cloud architectures and single-tenant, bare-metal deployments.
Develop and maintain GraphQL and REST APIs using Node.js, Express.js, and Apollo to handle complex data requirements.
Collaborate with the AI infrastructure team to integrate new GPU capabilities into our platform, utilizing Go (Golang) for high-throughput backend components.
Own features end to end, from design and implementation through deployment, monitoring, and iteration.
Instrument services with OpenTelemetry and build dashboards in Grafana to monitor performance and drive proactive optimization.
Who You Are:
An owner: You treat the product like it's yours and take accountability for outcomes, not just tickets.
A problem solver: You're energized by hard, ambiguous problems, and leverage first principles thinking to move the needle.
Customer-focused: You understand that the work matters because of the value it delivers to our users.
Proactive and self-driven: You are a T-shaped engineer who thrives in a lean startup environment; for you, stepping beyond the bounds of your role is second nature because you care deeply about solving hard problems and building resilient AI infrastructure at scale.
Essential Skills & Qualifications:
5+ years of professional software development experience.
Strong proficiency in React.js, Next.js (including SSR), and modern frontend development.
Strong knowledge of GraphQL and the Apollo ecosystem (Client, Server, schema design).
Solid foundation in Node.js and Express.js for building robust web applications.
Proven ability to drop into unfamiliar codebases, troubleshoot effectively, and solve complex problems independently.
Familiarity with Docker and containerization concepts.
Bachelor's degree in Computer Science or equivalent experience.
Preferred Skills & Qualifications:
Experience with Go (Golang) for building backend services, or a strong willingness to learn and adapt to Go-based tooling.
Experience with MongoDB, database design, and Redis for caching.
Understanding of Kubernetes (k8s), cloud infrastructure, and network fundamentals.
Experience with observability using OpenTelemetry (OTel) and Grafana-based stacks (PLG/MLG).
Python programming skills, particularly with FastAPI.
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 [email protected].
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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