Principal Automation and AI Operations Engineer

Position Overview:

Support definition, lifecycle management, and documentation of NAS and NCC SKUs within the Gateway and their integration with Q/V systems, eNB/gNB, BPMS, Networking, and OSS systems. Design automated test frameworks and scripts, drive pre- and post-deployment validation, and partner with engineering and service delivery teams on test plans, pass/fail criteria, field trials, and FOAs.

Key Responsibilities:

• Manage and document Gateway NAS and NCC SKUs.
• Build automated test frameworks for RF chain, baseband, BPMS, eNB/gNB, networking, and NCC/OSS interfaces.
• Validate Gateway SKUs against configuration and performance baselines.
• Partner with RF, hardware, and software teams on testing and field trials.
• Enable end-to-end Gateway visibility and management.
• Automate operating and engineering tasks and build remediation workflows.
• Integrate telemetry with decision engines and develop predictive models.
• Create automated incident triage and troubleshooting assistants.
• Establish guardrails for AI-driven operations and develop digital twins.
• Automate configuration validation and measure automation coverage.

Qualifications:

Education:

Bachelor's degree in computer science, computer engineering, electrical engineering, or a related technical field.

Experience:

• 5+ years in network automation, DevOps/SRE, or operations engineering.
• Experience building automated test frameworks, managing SKUs, supporting field trials, and working with network automation, infrastructure as code, event-driven systems, workflow automation, data engineering, machine learning, AIOps, autonomous remediation, digital twins, and policy-driven operations.
• Experience integrating telemetry pipelines with decision engines or remediation systems.

Preferred Qualifications:

• Highly autonomous operations models.
• NAS, NCC, core network, or OSS platforms.
• Predictive or ML-based failure detection and capacity planning.
• Satellite, RF, or baseband systems.
• Digital twins or simulation models.
• Governance for AI-driven operational actions.

Soft Skills:

Strong collaboration, communication, analytical, problem-solving, organizational, troubleshooting, and technical documentation skills, with the ability to manage multiple priorities independently.

Technology Stack:

Python, Go, Terraform, Ansible, event-driven and workflow-automation platforms, telemetry pipelines, streaming and message-bus systems, time-series databases, machine learning and AIOps platforms, digital-twin and simulation tooling, CI/CD, automated test frameworks, and NCC/OSS APIs.

Physical Requirements:

• Work in office, laboratory, and technical testing environments.
• Travel periodically for deployment, integration, testing, and operations.
• Safely handle technical equipment when necessary.
• Capture, analyze, and document technical test procedures, results, and performance data.