Staff Network Reliability Engineer, Service Assurance AIOps & Automation

📋 Job Overview

The world still has coverage blind spots. You could help eliminate them at Skylo. Skylo has pioneered a standards-based approach to satellite connectivity. We connect smartphones and IoT devices directly to satellites. No special hardware, no entirely new networks. Just billions of existing devices, suddenly reachable anywhere on Earth. We're not building toward this future. We're already in it.

Our direct-to-device service is live on millions of activated devices across five continents, covering more than 72 million square kilometers, in partnership with leading satellite operators, mobile network operators, Tier-1 chipset makers, and OEMs worldwide. And we're just getting started.

At the heart of it all is Skylo's commercial NTN vRAN: a 3GPP standards-based, cloud-native platform that seamlessly bridges terrestrial and satellite networks. It's the infrastructure that makes true anywhere, anytime connectivity possible.

When you join Skylo, you'll work at the intersection of three markets reshaping how the world stays connected: mass-market consumer devices, automotive, and industrial IoT. Enabling people outdoors and critical workflows in the world's most remote places.

This is a rare chance to work on technology that matters, at a company that's already proving it works

🏢 About Skylo

Skylo has pioneered a standards-based approach to satellite connectivity. We connect smartphones and IoT devices directly to satellites. No special hardware, no entirely new networks. Just billions of existing devices, suddenly reachable anywhere on Earth. We're not building toward this future. We're already in it.

Our direct-to-device service is live on millions of activated devices across five continents, covering more than 72 million square kilometers, in partnership with leading satellite operators, mobile network operators, Tier-1 chipset makers, and OEMs worldwide. And we're just getting started.

At the heart of it all is Skylo's commercial NTN vRAN: a 3GPP standards-based, cloud-native platform that seamlessly bridges terrestrial and satellite networks. It's the infrastructure that makes true anywhere, anytime connectivity possible.

🎯 The Role

As Staff AIOps & Automation Engineer within Global Product Support & Customer Success, you are the most senior technical authority for how Skylo automates the operation and engineering of its live NTN network. You own the reference architecture, the multi-year technical roadmap, and the engineering standards for a single centralized automation framework that both Network Operations (the NRE domain teams — Core, RAN, Cloud, and Incident Management) and Network Engineering consume for diagnostics, remediation, change, and validation.

Where the organization runs today on manual runbooks, repetitive engineering tasks, and alarm noise, you define the platform — and the operating model around it — that drives Skylo toward 80%+ autonomous incident resolution and engineering-grade, repeatable network change. You set the standard for DAG-based orchestration, the operational data layer, the AI-assisted automation tier model, and the governance that makes every automated action measurable, auditable, reversible, and trusted in production.

You are not measured by the scripts you personally ship; you are measured by an automation framework that scales as a repeatable operating system for the entire network organization — not heroics. This role reports into Network Engineering leadership and partners as a peer-level technical authority with the NRE domain leads, Ops Platform Engineering, Security, OSS/BSS, and the broader engineering organization.

✅ Key Responsibilities

• Automation Architecture & Technical Strategy: Own the end-to-end support and development of framework and multi-year roadmap for Skylo’s centralized network automation framework — the single platform that Network Operations (Core, RAN, Cloud, IM NRE teams) and Network Engineering consume for automated diagnostics, remediation, change, and validation.
• Serve as the design authority for the automation architecture review: set engineering standards, API contracts, data schemas, and governance guardrails that prevent automation fragmentation across domains and between Operations and Engineering.
• Define the platform extensibility model so domain NREs and network engineers compose domain-specific workflows from governed, reusable building blocks — without forking framework code or re-implementing primitives.
• Own build-vs-buy and tooling decisions (orchestration engine, data lake, observability stack, AI tooling), translating them into capital and run-cost implications for engineering leadership with a clear, defensible rationale.
• Establish the operating model around the framework: ownership boundaries, readiness gates, promotion criteria, and the cross-functional cadence that keeps Operations and Engineering aligned on one automation backlog rather than competing toolchains.
• Centralized Framework & Platform Engineering: Architect the centralized framework: reusable health-check modules, diagnostic libraries, remediation actions, and notification/escalation handlers — composable components with versioned, governed interfaces that domain teams chain into workflows.
• Define the automation API layer: standardized interfaces for alert ingestion (Pub/Sub, Prometheus Alertmanager), action execution (kubectl, GCP API, NF CLIs, network configuration interfaces), and result reporting (ITSM update, Slack, dashboard refresh).
• Set codebase and delivery standards: testing frameworks, CI/CD pipelines, linting, unit/integration tests, security scanning, and staged rollout via GitLab CI — and hold the organization to them through reference implementations and architecture review.
• DAG-Based Orchestration & Closed-Loop Automation: Define the DAG-based orchestration standard (Apache Airflow or equivalent): every workflow a composable, auditable pipeline of diagnostic steps, decision gates, remediation actions, and validation checks.
• Architect closed-loop automation for P3/P4 fault classes across both operations and engineering change: trigger → diagnostic DAG → root-cause classification → remediation → validation → auto-close with a full evidence trail and zero human touch for covered classes.
• Own the progressive automation tier model: Tier 1 (auto-diagnose and recommend), Tier 2 (auto-remediate with human approval), Tier 3 (fully autonomous closed-loop) — with confidence scoring and explicit promotion/demotion criteria based on measured incident outcomes.
• AI-Assisted Development & Intelligent Operations: Set the team standard for AI-assisted automation dev