AI Infrastructure Engineer

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.

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.