Lead Infrastructure Automation Engineer (SRE/AI)

About the role

Citi is hiring a senior, hands-on Individual Contributor Lead Infrastructure Automation Engineer in Heredia, Costa Rica. The role drives the firm's "No Ops" transformation by designing and building high-impact automation and Agentic AI solutions that reduce operational toil at enterprise scale. It is a strategic, long-term position focused on continuous evolution.

Key responsibilities

• Design and build the core frameworks for agentic AI and automation using platforms such as ARC, ServiceNow and Ansible, and create intelligent, event-driven systems that autonomously diagnose and remediate infrastructure issues.
• Build automated root cause analysis and self-healing capabilities for network and server infrastructure, correlating events from Netcool, Spectrum and Splunk to reduce MTTR.
• Re-engineer Change Management, Incident Task Management and hardware provisioning to be automation-first, using Infrastructure-as-Code and integrating SNOW, Ansible and ARC.
• Lead the absorption of the transferred L1 Application Support workstream and design shift-left solutions with other Foundational Services teams.
• Mentor junior analysts, evangelize automation-first principles and propose data-driven improvements to operational stability.

Required profile

• 7+ years in enterprise infrastructure, with a strong background in Network Operations or Systems Administration (Linux/Windows) in a 24/7 environment.
• Proven hands-on experience designing automation solutions that eliminate manual work.
• Experience applying AI/ML concepts to operational problems, including AIOps platforms (Moogsoft, Datadog AI) and agentic frameworks (ARC, LangChain, AutoGen).
• Preferred: SRE or DevOps experience, generative AI and LLMs use cases, familiarity with financial services or regulated industries, and relevant certifications (AWS/Azure/GCP, CKA, HashiCorp, CCNP, RHCE).

Required skills

• Advanced automation and IaC, especially Ansible and Terraform, with complex playbooks and modules.
• Strong Python scripting and API interaction.
• Observability platforms such as Splunk, Elastic, Prometheus or Grafana.
• Expert troubleshooting across network, server and application layers.