AI Developer

Job Description Role Overview

GLS is hiring a Full Stack Developer to build and maintain the internal tools and operational platforms that run our network business: monitoring dashboards, automation utilities, workflow tooling, and systems that integrate with live network/infrastructure APIs across a multi datacenter environment. This role is for someone who can ship quickly without sacrificing correctness – using modern AI developer tools (e.g., Claude Opus) and agent frameworks (e.g., Open Claw) to reduce cycle time, while still delivering reviewed, tested, production quality code.

Important:
We strongly support AI-assisted development. We do not want vibe coding (blindly accepting AI-generated diffs). We expect engineers to own outcomes through design, review, testing, security hygiene, and maintainability.

Internal operational tooling that engineers and NOC/SOC teams rely on daily. A custom monitoring/metrics platform spanning time-series data, dashboards, and alerting workflows. Integrations with live network/infrastructure APIs. Automation that reduces toil and speeds execution with auditability and guardrails.

• Design and implement backend services and REST APIs in Go and Python.
• Build durable internal services used for operational workflows and monitoring workloads.
• Create clean abstractions around infrastructure and device APIs.

• Build modern internal UIs in Angular for dashboards, tooling, and operational visibility.
• Deliver practical UX: fast, readable, and optimized for operators under pressure.

• Design schemas and write performant queries for PostgreSQL.
• Work with Click House (or similar columnar/time-series systems) for large-scale metrics.
• Optimize query patterns and data lifecycle for operational analytics and dashboards.

• Build software that interfaces with network/infrastructure APIs and operational platforms.
• Work closely with systems/network engineers to translate real-world requirements into reliable software.

• Build automation utilities using Python and Bash.
• Support Git-based workflows, CI/CD, and Git Ops conventions where appropriate.

AI-Assisted Engineering Expectations We expect you to use AI tools to move faster – and we measure success by quality shipped, not lines generated. You will:
Use AI developer tools (e.g., Claude Opus) for acceleration: scaffolding, refactors, test generation, troubleshooting, and documentation – while keeping engineering ownership and rigor. Apply agent frameworks (preferably Open Claw) to automate repeatable workflows (e.g., repo tasks, environment actions, operational runbooks), including safe execution models (tool policies / sandboxing / hooks or auditing patterns). Build and maintain guardrails: code review discipline, test coverage, static analysis, and secure-by-default patterns.

We do NOT want:
Vibe coding: accepting AI-generated code without understanding/reviewing/testing it.

Strong proficiency in Go, Python, and JavaScript/Type Script.

Hands-on Angular experience building internal dashboards/tools.

Strong PostgreSQL experience; exposure to Click House (or similar) preferred; familiarity with caching (e.g., Redis)

Comfortable in Linux environments; experience with Docker; basic Kubernetes/container familiarity;
Git-based workflows.

Proven experience building/consuming REST APIs and integrating with external/internal systems.

Git, Docker, Ansible (or similar configuration management).

Can work independently on loosely-defined problems and communicate clearly with infrastructure-focused teams.

The following skills and experience are not required but demonstrate valuable depth and would accelerate your impact in this role:

• Practical Open Claw experience: multi-agent setups, sandbox/tool allow/deny policies, hooks, automation patterns
• Git Ops tooling:
  ArgoCD, Fleet, Helm, operators
• Networking fundamentals: IP, VLANs, routing, firewall concepts
• Observability experience: metrics pipelines, time-series systems, log pipelines (e.g., Elasticsearch)