Software Engineer, Infrastructure
Full-time
Granica
Join Granica’s core engineering team to build and scale the infrastructure powering massive data systems, automated deployments, and high‑reliability AI workloads. This is a deep engineering role — not ops, not feature delivery. The infrastructure you build directly enables:
- exabyte‑scale data systems
- fast research‑to‑production cycles
- reliable enterprise AI workloads
This role offers deep ownership, high technical impact, and a long horizon.
What You’ll Do
- Design and operate cloud infrastructure supporting petabyte–exabyte‑scale systems.
- Manage and evolve production Kubernetes clusters with high availability and predictable scaling.
- Build and optimize CI/CD pipelines for faster builds, reliable tests, and safer deployments.
- Improve developer experience by reducing friction and automating workflows.
- Contribute to E2E testing and release‑confidence systems.
- Strengthen observability across logging, metrics, tracing, and alerting.
- Collaborate across engineering teams on architecture, reliability, and scaling challenges.
- Own customer‑facing technical integration — guide deployments, troubleshoot infra‑level issues in customer environments, and ensure Granica runs reliably within diverse cloud, data, and security stacks.
- Drive operational excellence through reliability, automation, and best practices.
What We're Looking For
- 5+ years in infrastructure, platform, or distributed systems engineering
- Strong coding skills in Go , Java , Python , or similar
- Production‑grade Kubernetes experience with strong cloud and containerization skills across AWS / GCP / Azure and Docker .
- Deep experience with CI/CD systems and cloud infrastructure
- Proficiency with infrastructure‑as‑code ( Terraform )
- Ability to debug complex, cross‑layer issues (networking, storage, runtime)
- Track record of designing scalable, reliable, cost‑efficient systems
- Thrives in fast‑paced startup environments with strong communication and ownership.
Nice-to-Haves
- Experience with data platforms or lakehouse systems
- Familiarity with Spark , Trino , Iceberg , Delta , Airflow
- Exposure to observability stacks ( Prometheus , Grafana , ELK , Datadog )
Vacancy posted 2 days ago
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