Staff Network Reliability Engineer, Service Assurance AIOps & Automation

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

Summary: How you will impact Skylo

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 development — Claude Code, Claude Cowork, and GitHub Copilot as workflow-integrated force multipliers — and personally prototype reference implementations to prove the bar: from problem statement to staged prototype in hours, not weeks.

• Architect AI-powered diagnostic agents and alert-correlation engines that correlate Core NF, RAN, Cloud, and OSS signals into actionable root-cause hypotheses and suppress alarm storms — grounded in trusted data, measurable accuracy, and auditability, not novelty.

• Make AI a structural part of the operating model — how the organization detects, isolates, resolves, reports, and learns — with human-in-the-loop gates, model/agent governance, and explicit thresholds for operational trust.

Data Engineering & Operational Intelligence

• Architect the real-time data pipelines and the operational data lake (BigQuery or equivalent): structure telemetry, incident records, KPI time-series, and automation execution logs into queryable, governed datasets that enable trend analysis, capacity forecasting, and automation-effectiveness measurement.

• Set DataOps standards: version-controlled pipeline definitions, automated data-quality checks, schema-evolution management, and pipeline health monitoring — the data layer must be as reliable as the network it observes.

• Define the dashboarding and analytics standard (Grafana): high-fidelity operational views for NRE teams, network engineers, Incident Managers, and executive leadership, built from a single governed data layer.

Governance, Security & Operational Readiness

• Enforce automation governance: every automated action has a defined rollback path, human-in-the-loop validation for P1/P2 actions, audit logging, and safe-handoff to humans when confidence falls below threshold.

• Build security into the operating model: least-privilege identity for automation actors, secrets management, full audit trails on production-changing actions, controlled partner/vendor access, and security exceptions that are explicit, time-bound, owned, and visible.

• Account for downstream blast radius: ensure automated actions that touch provisioning, inventory, entitlement, assurance, or reporting are designed without creating OSS/BSS or revenue-assurance operational debt.

Organizational Leadership & Cross-Functional Partnership

• Act as the automation intake and design authority for all NRE domain teams and Network Engineering: convert surfaced toil and engineering pain into prioritized, measurable automation with defined MTTA/MTTR targets and owners.

• Partner with Ops Platform Engineering on shared event schemas, API contracts, and policy engines; partner with Security, OSS/BSS, and Customer Operations to validate operational impact before rollout.

• Mentor and raise the bar for Staff and Senior automation developers; establish the technical-leadership and review pipeline for network automation across all hubs.

• Drive continuous improvement: track automation coverage, MTTA/MTTR impact per workflow, false-positive rate, human-override frequency, and adoption — every automation is measured, not assumed.

Qualifications

Required

• 14+ years in platform automation, observability/SRE tooling, service assurance development, or network automation engineering — including 4+ years operating at a Principal / Staff-plus / Architect level owning org-wide automation or platform architecture in a 24×7 production environment.

• Demonstrated track record architecting a centralized automation or platform framework consumed by multiple operations and/or engineering teams: reference architecture, API and schema governance, and an extensibility model that prevented fragmentation.

• Expert software development in Python (primary) with production-grade discipline — modular architecture, testing, CI/CD integration, and code review; Go a strong plus.

• Deep DAG-based workflow orchestration mastery: Apache Airflow, Prefect, Dagster, or equivalent — multi-step pipelines with branching, error handling, retry, and human-in-the-loop gates.

• Data engineering at architecture level: real-time streaming (Pub/Sub, Kafka), data lake design (BigQuery or equivalent), schema design, DataOps, and data-quality governance.

• Production observability stack ownership: Prometheus (PromQL, recording and alerting rules), Grafana, VictoriaMetrics, and log aggregation (Loki or ELK).

• AI-assisted development as a daily accelerator — Claude Code, Claude Cowork, GitHub Copilot, or equivalent — with the judgment to set team standards for safe, auditable AI-in-the-loop automation.

• Kubernetes and cloud-native architecture (GKE or EKS), Helm authorship, and GitOps via ArgoCD; CI/CD pipeline design (GitLab CI or Jenkins) with security scanning and rollback.

• Alert correlation and event processing at scale, plus governance, audit, and security design for production-changing automation.

• Executive-grade communication: translate operational and engineering toil into architecture and an operating model, and present automation impact and roadmap to engineering leadership.

Preferred

• Automation for telecom or NTN network operations and engineering: 5G Core, RAN, and cloud-infrastructure alarm patterns plus network-engineering change and validation workflows.

• Agentic AI development: LLM-powered diagnostic agents, automated RCA assistants, or AI-driven operational copilots.

• ServiceNow or Jira automation (API-driven ticket lifecycle, workflow automation, bot integration) and advanced Grafana development (custom plugins, dashboard governance).

• Chaos engineering and automated resilience testing; DataOps/MLOps practices (feature stores, model serving, experiment tracking, pipeline versioning) for operational ML.

• OSS/BSS integration awareness for provisioning, assurance, inventory, and reconciliation impacts.

• Certifications: CKA, AWS/GCP Professional, Confluent Kafka, or Apache Airflow certification

What We Offer

With employees working across three continents, Skylo is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. Our worldwide and inclusive culture encourages a flexible approach to work, and we also offer an attractive range of benefits such as:

• Competitive compensation packages including a stock option based equity program

• Comprehensive benefits plans

• Monthly allowances for wellness and education reimbursement

• A generous time off policy, holidays, and the opportunity to temporarily work abroad

• Once-in-a-lifetime opportunity to be part of developing and running the world’s first commercial, live direct-to-device satellite network and service

• Access to a world-class team and talent across tech domains: software, hardware, chipsets, telecom, satellite and network virtualization

• Open, transparent, inclusive culture that blends Silicon Valley, Nordic and South Asia characteristics

EEO Statement

Skylo is an equal-opportunity employer and we celebrate diversity. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, parent or caregiver status, political affiliation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service consistent with applicable federal, state, and local laws.

We are also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. Please let us know if you need assistance or accommodation due to a disability.