AI Development Lead - Infrastructure & Automation

CRC Group•Charlotte, NC

1d•Onsite

About The Position

The AI Development Lead – Infrastructure & Automation is a senior technical leadership role responsible for building and scaling AI-driven infrastructure automation across Enterprise Technology & Operations. Reporting to the CTO, this role will own agent-based development, platform integrations, and AI-enabled operations spanning network operations, cloud management, service management, and internal developer platforms. This leader will manage multiple highly technical development teams and is expected to be hands-on, opinionated, and deeply technical. The ideal candidate is energized by working with emerging, fast-moving AI tooling and excels at integrating AI capabilities directly into enterprise infrastructure, operations, and control planes—not just application layers. The role sits at the intersection of platform engineering, infrastructure operations, and applied AI, translating novel AI capabilities into reliable, secure, observable, production-grade systems.

Requirements

Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
8+ years of deep technical engineering experience, with proven hands-on team leadership.
Strong background in infrastructure, platform engineering, or SRE, not just application development.
Demonstrated experience building and operating automation or AI-driven operational systems.
Deep familiarity with: Cloud platforms (Azure preferred), Infrastructure as Code (Terraform, ARM/Bicep, etc.), Containers and platforms (Kubernetes, Docker), CI/CD pipelines and developer platforms
Practical experience with LLMs, agents, or automation frameworks, including: LLM integration and orchestration, Agent-based workflows, Retrieval and context systems
Proven ability to lead teams building production-grade systems, not experiments.

Nice To Haves

Experience using advanced AI developer tools (Foundry-style platforms, AI-driven coding agents).
Experience integrating AI into: Network operations, Cloud governance, IT Service Management platforms
Background in high-velocity environments.
Master’s degree or advanced certifications in cloud, AI, or infrastructure engineering.

Responsibilities

Architect, build, and operate AI agents that monitor, manage, and remediate: Network and infrastructure operations, Cloud platforms and cost/usage optimization, Service management (incident, problem, change, request), Platform health, availability, and performance
Design event-driven and agentic architectures that integrate AI agents directly into operational workflows and tooling.
Lead development of AI copilots and autonomous systems embedded in infrastructure and operations platforms.
Drive adoption and production use of cutting-edge AI and development platforms, including: Microsoft Foundry and Azure-native AI tooling, Codex-style AI-assisted development and automation, Claude Code and other advanced agent-oriented coding systems
Continuously evaluate emerging tools, frameworks, and orchestration patterns for applied enterprise AI.
Lead deep integrations between AI services and: Cloud platforms (Azure-first, multi-cloud where required), Network management and monitoring systems, IT Service Management (ITSM) platforms, Observability, logging, and telemetry platforms
Ensure AI solutions are designed for production resiliency, auditability, and enterprise operability.
Partner closely with infrastructure, cloud, network, security, and service management teams.
Lead and scale multiple development teams (AI engineers, platform engineers, automation engineers).
Set engineering standards for: Agent development and lifecycle management, CI/CD and Infrastructure as Code, Secure-by-design AI services, Observability and runtime monitoring of AI systems
Stay hands-on with architecture, critical design decisions, and complex implementations.
Establish standards for: AI runtime monitoring, drift detection, and performance tracking, Secure prompt, model, and data handling, Responsible AI usage within operational systems
Ensure AI-enabled infrastructure solutions meet enterprise requirements for: Security, compliance, and resilience, Change management and auditability, Hybrid and multi-cloud support