Ai Full Stack Developer Jobs in Concord, NC (NOW HIRING)

Full Stack Developer (AI-Accelerated)

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 infrastructure 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) and agent frameworks 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.

What You'll Build

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 (devices, services, systems). Automation

that reduces toil and speeds execution with auditability and guardrails.

Key Responsibilities

Backend Engineering (Go + Python)

• 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.

Frontend Engineering (Angular)

• Build modern internal UIs in Angular for dashboards, tooling, and operational visibility.

• Deliver practical UX: fast, readable, and optimized for operators under pressure.

Full Stack Developer (AI-Accelerated) — Internal Tools & Network Platforms

Data & Database Engineering (PostgreSQL + ClickHouse)

• Design schemas and write performant queries for PostgreSQL.

• Work with ClickHouse (or similar columnar/time-series systems) for large-scale metrics.

• Optimize query patterns and data lifecycle for operational analytics and dashboards.

Infrastructure Integration

• 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.

Automation & GitOps Workflows

• Build automation utilities using Python and Bash.

• Support Git-based workflows, CI/CD, and GitOps 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) for

acceleration: scaffolding, refactors, test generation, troubleshooting, and documentation

— while keeping engineering ownership and rigor. Apply agent frameworks

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.

Required Skills & Qualifications

Skill Category Requirements

Languages Strong proficiency in Go, Python, and

JavaScript/TypeScript.

Frontend Hands-on Angular experience building

internal dashboards/tools.

Databases Strong PostgreSQL experience; exposure to

ClickHouse (or similar) preferred;

familiarity with caching (e.g., Redis).

Full Stack Developer (AI-Accelerated) — Internal Tools & Network Platforms

Skill Category Requirements

Linux & Delivery Comfortable in Linux environments;

experience with Docker; basic

Kubernetes/container familiarity; Git-based

workflows.

API Engineering Proven experience building/consuming

REST APIs and integrating with

external/internal systems.

Tooling Git, Docker, Ansible (or similar

configuration management).

Communication Can work independently on loosely-defined

problems and communicate clearly with

infrastructure-focused teams.

Nice to Have (Strong Signals)

The following skills and experience are not required but demonstrate valuable depth and

would accelerate your impact in this role:

• Practical experience: multi-agent setups, sandbox/tool allow/deny policies,

hooks, automation patterns

• GitOps tooling: ArgoCD, Fleet, Helm, operators

• Networking fundamentals: IP, VLANs, routing, firewall concepts

• Observability experience: metrics pipelines, time-series systems, log pipelines (e.g.,

Elasticsearch)

What Success Looks Like (First 60–90 Days)

• Ship meaningful improvements to internal tooling and/or monitoring workflows.

• Deliver at least one end-to-end feature: UI + API + database + operational integration.

• Improve cycle time using AI tools with discipline: tests, review, measurable reliability

gains.

• Contribute reusable automation patterns that reduce toil for the team (agent or script-

based).

Full Stack Developer (AI-Accelerated) — Internal Tools & Network Platforms

Why GLS

You'll build software that directly supports real operational outcomes. Real users, real

systems, real impact. High ownership, low bureaucracy, strong technical collaboration with

infrastructure experts.

How to Apply

If you're excited about building mission-critical internal tools with modern AI-assisted

workflows while maintaining engineering rigor, we'd love to hear from you. Submit your

resume and a brief note about your experience with full-stack development, particularly

highlighting any AI-accelerated development practices you've used. Include links to relevant

projects or code samples if available.