About The Role

Parallel Wireless is a U.S.-based pioneer in Open RAN innovation, transforming how mobile networks are built, optimized, and powered. Through our GreenRAN™ portfolio, we enable operators to deliver next-generation connectivity with unmatched energy efficiency, automation, and flexibility.

What you need -

8+ years of hands-on DevOps, SRE, or platform engineering experience, including ownership of production systems at scale.
Strong experience with cloud platforms such as AWS, Azure, Google Cloud, or on-prem Kubernetes solutions.
Strong experience with containerization and orchestration (Docker, Kubernetes).
Proficiency in writing and maintaining Helm charts, including chart libraries, subcharts, and versioning strategy.
Strong programming skills in cloud-native environments, preferably Go/C/C++/Python
Solid knowledge of networking concepts, DNS and load balancing.
Strong understanding of security best practices and DevSecOps principles (secrets management, supply chain security, image scanning, least-privilege IAM).
Familiarity with monitoring, logging, and tracing tools (Prometheus, Grafana, ELK/OpenSearch, Loki, OpenTelemetry).
Working knowledge of AI-assisted development tools across the SDLC — using AI coding assistants and agents (e.g., for code generation, refactoring, test writing, debugging, and code review) to improve development speed and quality, with sound judgment on validating and reviewing AI-generated output.

Job description -

Design, build, and maintain scalable and secure infrastructure for applications across development, testing, and production environments.
Automate provisioning, configuration, and monitoring using Infrastructure as Code tools such

as Terraform, Ansible, or CloudFormation.

Manage and optimize container orchestration platforms (Kubernetes, EKS, AKS, GKE, or on-prem).
Integrate and manage open source components such as storage provisioners, ingress and load balancers, container registries, and certificate management.
Create Helm charts and deploy consistently across multiple platforms and environments.
Design, develop, and maintain microservices that drive edge cluster orchestration.
Leverage AI tools throughout the SDLC — from design and coding to testing, documentation, and troubleshooting — to accelerate delivery while ensuring output is reviewed, validated, and production-ready.