JOB DESCRIPTION

Key Responsibilities

Systems Integration & Reliability

• Deploy, configure, and validate edge computing systems across lab, field, and production environments.
• Integrate and optimize system components spanning embedded hardware, networking, containerization, and cloud APIs.
• Collaborate with software, infrastructure, and field teams to identify and resolve integration and runtime issues.
• Ensure reliable device-to-cloud communication for telemetry, control, and analytics workloads.

Troubleshooting & Diagnostics

• Perform end-to-end triage across hardware, network, and application layers.
• Use Linux CLI tools, container inspection, and telemetry analysis to isolate and correct complex system failures.
• Reproduce field issues in controlled environments and contribute findings back into engineering processes.
• Develop reusable diagnostic tools and test harnesses to validate system resilience.

Automation & Observability

• Build and maintain monitoring, and recovery automation (e.g., Bash, Python, Go).
• Contribute to orchestration frameworks such as Docker, K3s, or Kubernetes for edge deployments.
• Enhance observability through metrics, dashboards, and alerting (Datadog, Grafana, Prometheus, etc.).
• Identify opportunities for self-healing and reliability automation.

Knowledge Management

• Author and maintain runbooks, standard operating procedures, and knowledge base articles.
• Document troubleshooting procedures and design patterns to enable Tier 1 and Tier 2 support efficiency.
• Participate in post-incident reviews and translate lessons learned into durable operational improvements.

Collaboration & Escalation

• Partner with software engineers, DevOps, and operations teams to drive incident resolution.
• Act as a 24x7 escalation SME for complex edge or connectivity issues.
• Leverage escalation learnings to define and drive system reliability and lifecycle management initiatives.

Safety

• Adhere to all NOV HSE policies, utilize appropriate PPE, and actively participate in monthly safety meetings.

Qualifications

Required

• Bachelor's degree in Computer Engineering, Computer Science, Information Systems, or equivalent work experience
• 3-5 years minimum relevant experience
• Strong proficiency with Linux systems and command-line diagnostics.
• Experience with containerized environments (Docker, K3s, or Kubernetes).
• Understanding of IoT or distributed systems architectures, including secure communication (TLS/mTLS).
• Solid grasp of networking fundamentals: IP, routing, VPNs, DNS, and cellular/LTE connectivity.
• Scripting ability in Bash, Python, or Go for automation and tooling.
• Demonstrated ability to troubleshoot across hardware, network, and software boundaries.
• Excellent written communication skills; comfortable producing procedural documentation.

Preferred

• Experience in industrial or edge computing environments (IoT gateways, embedded Linux, or ruggedized hardware).
• Familiarity with GitOps workflows, CI/CD pipelines, or infrastructure-as-code tools.
• Exposure to observability platforms such as Datadog, Grafana, or Prometheus.
• Background in site reliability, DevOps, or systems integration roles supporting production systems.

Ideal Profile

You are a multidisciplinary engineer who:

• Moves fluidly between hardware, software, and networking domains.
• Believes operational excellence and reliability are core features of a product.
• Automates repetitive work and documents what cannot be automated.
• Brings composure, curiosity, and methodical problem-solving to complex technical challenges.

Why This Role Matters

Edge computing is rapidly redefining how distributed systems are deployed and managed.

The Edge Systems Engineer ensures those systems are reliable, observable, and maintainable - providing the connective tissue between development, infrastructure, and real-world operations.