AI Infrastructure Engineer

AI Infrastructure Engineer
Location: Fort Mill, SC
Forward Deployed AI Engineer (FDE)
LPL - AI Engineering & Infrastructure Transformation Engagement

About the Role:
Client is building a Forward Deployed AI Engineering team to support LPL's move to an AI-first infrastructure organization. The goal is to embed AI engineers directly across LPL's infrastructure teams, build a centralized AI engineering pool that can rapidly solve business problems, and automate manual infrastructure processes wherever possible.
Early AI initiatives on the account have already delivered a 60% reduction in migration effort, a 50% reduction in modernization effort, and an automated vulnerability discovery and remediation pipeline. These engineers are expected to act as transformation catalysts - not traditional developers - using AI as the first approach to solving problems and inspiring the existing engineering teams around them.


Target infrastructure domains

• Cloud
• Network
• Compute
• Storage
• Database Platforms
• Infrastructure Security
• Automation

Purpose
Work directly with LPL infrastructure teams to identify opportunities, build AI-powered solutions, automate manual processes, and accelerate engineering productivity.


Key Responsibilities

• Embed within infrastructure teams and work closely with business and infrastructure leaders.
• Identify automation opportunities independently, without waiting for instructions.
• Build AI-assisted solutions using Cursor and GitHub Copilot.
• Develop infrastructure automation and build AI workflows and AI agents.
• Modernize infrastructure platforms and improve cloud migration efficiency.
• Build vulnerability remediation automation.
• Demonstrate proof-of-concepts rapidly and deliver measurable productivity improvements.
• Mentor existing engineering teams and promote AI adoption across the organization.

Required Skills & Experience

• Programming & scripting: strong Python development, scripting, and APIs.
• Infrastructure & cloud: infrastructure engineering, cloud platforms (AWS preferred), Infrastructure as Code (IaC), DevOps, and automation.
• AI-assisted engineering: GitHub Copilot, Cursor AI, prompt engineering, LLM-based software development, and AI-assisted coding.
• Ways of working: strong problem solving, a self-starter mindset, and excellent communication.

Preferred Skills

• Agentic AI workflows and AI orchestration
• Infrastructure modernization and platform engineering
• Security automation and vulnerability management
• FinOps and observability
• Cloud migration

Platform & Infrastructure FDE
Depth in the platforms, pipelines, and guardrails that AI-driven infrastructure runs on.

• Infrastructure as Code - Terraform, Pulumi, AWS CDK, VMware, OpenShift
• Configuration-as-Code - Ansible, Puppet
• CI/CD - GitHub Actions, ArgoCD
• Kubernetes - EKS / GKE / AKS, Helm, service mesh
• Observability - OpenTelemetry, Dynatrace, Grafana, LLM metrics
• Cloud security - VPC, PrivateLink, encryption, data residency
• Compliance - SOC 2, HIPAA, FedRAMP for LLM
• Agentic frameworks - LangGraph, CrewAI, N8N
• LLMOps - model routing (LiteLLM), semantic caching, prompt versioning, A/B testing
• Cost / FinOps for LLM

Agentic Systems FDE
Depth in designing, orchestrating, and evaluating reliable multi-agent AI systems.

• Agentic frameworks - LangGraph, CrewAI, AutoGen, Anthropic computer-use
• Tool / function calling
• Orchestration & state - retry, checkpointing, failure modes
• Multi-agent patterns
• Memory systems - short-term, long-term vector, episodic
• Human-in-the-loop approval workflows
• Non-deterministic output evaluation
• Tracing - LangSmith, Arize, OpenTelemetry

Principal FDE (future / escalation profile)
Not part of this hiring wave, but the likely escalation profile as the engagement scales.

• End-to-end enterprise AI architecture
• Provider trade-offs - Anthropic vs. Bedrock vs. Vertex vs. Azure
• AI governance and build-vs-buy decisions
• ROI / KPI ownership
• Executive presence with CTO / CDO / CFO stakeholders

Desired Behavioral Traits

• AI-native mindset - uses AI as the first approach to solving problems
• Highly proactive; identifies opportunities and builds automation without being asked
• Curious, innovative, and an independent thinker
• Strong collaborator, comfortable working with ambiguity
• Outcome-focused; delivers measurable productivity gains rather than incremental ones
• Able to influence and mentor others, acting as a transformation catalyst

Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.