AI Infrastructure Engineer

AI Infrastructure EngineerLocation: Fort Mill, SC - OnsiteDuration: Long Term ContractTarget infrastructure domains:CloudNetworkComputeStorageDatabase PlatformsInfrastructure SecurityAutomationPurpose: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 orchestrationInfrastructure modernization and platform engineeringSecurity automation and vulnerability managementFinOps and observabilityCloud migrationPlatform & Infrastructure FDE:Depth in the platforms, pipelines, and guardrails that AI-driven infrastructure runs on.Infrastructure as Code — Terraform, Pulumi, AWS CDK, VMware, OpenShiftConfiguration-as-Code — Ansible, PuppetCI/CD — GitHub Actions, ArgoCDKubernetes — EKS / GKE / AKS, Helm, service meshObservability — OpenTelemetry, Dynatrace, Grafana, LLM metricsCloud security — VPC, PrivateLink, encryption, data residencyCompliance — SOC 2, HIPAA, FedRAMP for LLMAgentic frameworks — LangGraph, CrewAI, N8NLLMOps — model routing (LiteLLM), semantic caching, prompt versioning, A/B testingCost / FinOps for LLMAgentic Systems FDE:Depth in designing, orchestrating, and evaluating reliable multi-agent AI systems.Agentic frameworks — LangGraph, CrewAI, AutoGen, Anthropic computer-useTool / function callingOrchestration & state — retry, checkpointing, failure modesMulti-agent patternsMemory systems — short-term, long-term vector, episodicHuman-in-the-loop approval workflowsNon-deterministic output evaluationTracing — LangSmith, Arize, OpenTelemetryPrincipal FDE (future / escalation profile):Not part of this hiring wave, but the likely escalation profile as the engagement scales.End-to-end enterprise AI architectureProvider trade-offs — Anthropic vs. Bedrock vs. Vertex vs. AzureAI governance and build-vs-buy decisionsROI / KPI ownershipExecutive presence with CTO / CDO / CFO stakeholdersDesired Behavioral Traits:AI-native mindset — uses AI as the first approach to solving problemsHighly proactive; identifies opportunities and builds automation without being askedCurious, innovative, and an independent thinkerStrong collaborator, comfortable working with ambiguityOutcome-focused; delivers measurable productivity gains rather than incremental onesAble to influence and mentor others, acting as a transformation catalystDiverse 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.