Infrastructure Engineer

Designs, implements, and manages AWS cloud infrastructure, including VPCs, EC2, RDS, S3, IAM, Lambda, and other foundational services.

Develops and maintains Terraform modules to provision and manage infrastructure in a repeatable, version-controlled manner.

Deploys, manages, and optimizes Kubernetes clusters (EKS), handling workload orchestration, autoscaling, and resource management.

Builds and improves continuous integration and deployment (CI/CD) pipelines to enable fast, safe, and automated releases.

Implements logging, monitoring, and alerting solutions to ensure system health and enable rapid incident response.

Applies strict infrastructure security best practices, manages secrets, and ensures compliance with internal security policies.

Writes scripts and tools to automate operational tasks, reducing manual toil and improving the overall developer experience.

Creates and maintains runbooks, architecture diagrams, and technical documentation.

Partners with development teams to improve platform reliability and streamline application deployments.

Participates in an on-call rotation schedule to respond to production incidents and ensure continuous system reliability.

Designs and provisions cloud infrastructure specifically tailored to support scalable AI/LLM workloads and agentic systems, ensuring optimized compute resource allocation and high availability.

Evaluates and integrates AI-driven DevOps tools and LLM-assisted automations into the platform workflow to accelerate incident response, infrastructure provisioning, and operational troubleshooting.

Location: This role is fully remote and open exclusively to candidates based in LATAM.

Experience:

• 4+ years of proven experience in infrastructure, DevOps, or platform engineering.

• Strong proficiency with AWS services and modern cloud architecture patterns.

• Hands-on experience utilizing Terraform for Infrastructure as Code (IaC).

• Solid understanding of Kubernetes concepts (deployments, services, ingress, RBAC, Helm charts) and containerization utilizing Docker.

• Proficiency in TypeScript and Bash scripting.

• Familiarity with standard CI/CD tools (e.g., GitHub Actions, GitLab CI, ArgoCD).

• Strong understanding of networking fundamentals (DNS, load balancing, firewalls, VPNs).

• Hands-on experience provisioning infrastructure for AI agent frameworks (e.g., LangChain, LlamaIndex, CrewAI) or deploying LLMs in a production or near-production context.

• Strong troubleshooting, problem-solving, and cross-functional communication skills.

Nice to Have:

• Experience coding in Golang.

• Knowledge of GitOps practices and tools (ArgoCD, Flux).

• Familiarity with modern observability stacks (Prometheus, Grafana, Datadog, ELK).

• AWS certifications (Solutions Architect, DevOps Engineer) or Kubernetes certifications (CKA/CKAD).

• Experience with service mesh implementations (Istio, Linkerd) and FinOps practices for cost optimization.