Description

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

Key Skills

Education

Any Graduate