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AI infrastructure Engineer (Infrastructure as Code)
EdgeAllFort Mill, SC🇺🇸United StatesPosted 16 Jul 2026
Quick Overview
Work Type
Hybrid
Level
Mid Senior
Job Description
Job Summary: We are seeking a proactive and innovative AI Infrastructure Engineer to work directly with our LPL infrastructure teams. The ideal candidate will identify opportunities for automation, build AI-powered solutions, and enhance engineering productivity. This role requires a strong foundation in Python development, infrastructure engineering, and a deep understanding of GitHub tools.
Responsibilities:
- Embed within infrastructure teams to understand workflows and identify automation opportunities.
- Independently identify and implement automation solutions.
- Build AI-assisted solutions utilizing Cursor and GitHub Copilot.
- Develop infrastructure automation processes to streamline operations.
- Create AI workflows and AI agents to enhance productivity.
- Modernize existing infrastructure platforms for improved performance.
- Enhance cloud migration efficiency through innovative solutions.
- Automate vulnerability remediation processes.
- Mentor existing engineering teams on best practices and AI adoption.
- Promote AI adoption across the organization to drive efficiency.
- Deliver measurable productivity improvements through automation.
- Rapidly demonstrate proof-of-concepts to stakeholders.
- Collaborate closely with business and infrastructure leaders to align on goals.
Mandatory Skills:
- Strong proficiency in Python development.
- Experience in infrastructure engineering.
- Familiarity with cloud platforms, preferably AWS.
- Expertise in Infrastructure as Code (IaC).
- Proficient in GitHub Copilot and Cursor AI.
- Knowledge of prompt engineering and LLM-based software development.
- Experience with AI-assisted coding practices.
- Strong understanding of DevOps principles and automation.
- Proficient in APIs and scripting.
- Excellent problem-solving skills and a self-starter mindset.
- Strong communication skills to convey complex ideas effectively.
Preferred Skills:
- Experience with agentic AI workflows and AI orchestration.
- Knowledge of infrastructure modernization techniques.
- Familiarity with security automation and vulnerability management.
- Understanding of FinOps and observability practices.
- Experience in platform engineering and cloud migration strategies.
Qualifications:
- 3-5 years of relevant experience in AI infrastructure engineering.
- Proven track record of delivering automation solutions that reduce manual effort.
- Demonstrated ability to influence and mentor engineering teams.
- Strong collaborative skills and ability to work in ambiguous environments.
- Outcome-focused with a commitment to driving measurable improvements.
Success Measures:
- Reduction of manual effort by 50-70% through automation.
- Increased AI adoption across teams and projects.
- Successful delivery of infrastructure automation initiatives.
- Faster project execution and improved engineering productivity.
- Positive influence on engineering culture and practices.
Desired Behavioral Traits:
- AI-native mindset with a passion for innovation.
- Highly proactive and curious about emerging technologies.
- Independent thinker who can navigate ambiguity.
- Strong collaborator with the ability to influence others.
- Outcome-focused and committed to achieving results.
Skills
AWS
LLM
Python
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