Manage and lead a team of engineers in developing cloud applications and architectures, optimizing performance, and supporting product delivery in a telecommunications environment.
Parallel Wireless is reimagining mobile networks with innovative, energy-efficient Open RAN solutions. Join us as we lead the future of telecommunications, driving innovation through green and sustainable networks. Learn more about our mission, vision and values.
We’re looking for a motivated and experienced Cloud Applications Team Manager to drive innovation and lead engineering team. In this role, you'll shape cloud-native architectures, optimize performance, and spearhead cutting-edge development in a fast-paced environment.
What you will do:
- Managing a team of 3-4 engineers, focused on the development of cloud environment and applications.
- Technical leadership and mentorship to junior engineers within the team, fostering skill development and knowledge sharing.
- Elevate the team to industry-standard software development methods.
- Design and development of RIC/xApp/rApp software aimed to leverage our cluster-level awareness.
- Facilitate optimization of cellular infrastructure applications on cloud-based X86 & ARM platforms.
- Support product delivery activities and PoCs (Proof of Concept).
- Evaluating product performance.
What you should have:
- 5+ years of experience in software development, with at least 2 years in a leadership role, including hiring software professionals and building a highly performing team.
- Strong programming skills in C/C++/GO.
- Experience with cloud-native architectures, Kubernetes, DB, and container orchestration.
- Ability to read and interpret technical specifications, and translate them into actionable software requirements and development plans
- Proficiency in microservices development, API design, and messaging frameworks (Kafka, gRPC, REST, etc.).
- Experience with CI/CD tools like Jenkins, GitLab, Helm, Terraform - advantage
- Familiarity with of O-RAN architecture, RIC platforms, and E2 interface protocols - advantage
- Excellent leadership and communication skills to guide a team in a fast-paced, agile environment.
- Systematic problem-solving approach, coupled with a sense of ownership and drive.
- Familiarity with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) for RAN optimization - advantage
Education:
- B.Sc./M.Sc/B.Tech/M.Tech in Computer Science or Electrical Engineering
Parallel Wireless is expanding the ecosystem for Open RAN with the GreenRAN™ energy-efficient Hardware-Agnostic technology. Deployed worldwide, our comprehensive 2G/3G/4G/5G Macro RAN solutions enhance network security while reducing operating expenses. As pioneers of Open RAN, we prioritize innovation, flexibility, and sustainability to help build a more connected, and green networks. Headquartered in the USA with global R&D centers, we are proud to serve over 60 customers worldwide and have been recognized with over 100 industry awards. Our mission is to accelerate GSMA’s Mobile Net Zero initiative by reducing TCO and driving innovation across the telecom ecosystem.Learn more at www.parallelwireless.com.
Parallel Wireless embraces diversity and equality of opportunity. We are committed to building inclusive and diverse teams representing all backgrounds, with a wide range of perspectives, and empowering industry-leading skills. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.Parallel Wireless does not accept unsolicited resumes or applications from agencies or individuals. Please do not forward resumes to our jobs alias, Parallel Wireless employees, or any other company location. Parallel Wireless is not responsible for any fees related to unsolicited resumes/applications.
Top Skills
Ai/Ml Frameworks
C/C++
Ci/Cd Tools
Db
Docker
Gitlab
Go
Grpc
Helm
Jenkins
Kafka
Kubernetes
PyTorch
Rest
Scikit-Learn
TensorFlow
Terraform
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