Principal Infrastructure Engineer (Contract – LATAM)

About Nexus

Nexus is building the AI gateway for modern companies — one platform that gives teams access to the world's leading AI models while keeping costs predictable, security under control, and workflows connected.

Companies can use Nexus to access models like GPT, Claude, Gemini, and many others through a unified platform. Our infrastructure helps organizations choose the right model for each task, manage usage and budgets, enforce access policies, and integrate AI into the tools their teams already use.

Headquartered in San Francisco with a growing presence in Latam, Nexus is a cross-continental team building the infrastructure that makes AI more accessible, efficient, and manageable at scale.

We're investing deeply in the Latin American engineering ecosystem and looking for exceptional talent to help us build the next generation of AI infrastructure.

Nexus is backed by leading investors, including Pantera, Lightspeed, Dragonfly, Faction, Blockchain Builders Fund, Alliance, and SVA.

We’re expanding our infrastructure engineering team in Latin America to build and scale the platform powering Nexus’s AI gateway.

We’re looking for Infrastructure Engineers who enjoy building reliable, secure, and highly available systems that run in production at scale.

You’ll help design and operate the infrastructure behind our platform, from the cloud environments and deployment pipelines that run our services to the networking, observability, and security layers that keep AI traffic flowing reliably for enterprise customers.

This role combines cloud infrastructure, distributed systems, and emerging AI technologies. You’ll work on systems where uptime, latency, and cost efficiency matter, helping companies access and manage multiple AI models through a single platform.

You’ll collaborate closely with engineering and product teams in San Francisco while contributing remotely from Latin America.

What You'll Do

• Design, build, and maintain the cloud infrastructure powering Nexus’s AI gateway.

• Operate and scale containerized services with Kubernetes across multiple environments and regions.

• Build and maintain Infrastructure-as-Code, CI/CD pipelines, and deployment workflows.

• Develop observability for high-volume AI traffic, including metrics, tracing, logging, alerting, and SLOs.

• Ensure high availability, failover, and resilience for services that route requests to multiple AI providers.

• Implement security best practices, including network isolation, secrets management, access controls, and the compliance needs of enterprise customers.

• Optimize infrastructure performance and cloud costs as usage grows.

• Participate in incident response, root cause analysis, and continuous reliability improvements.

• Collaborate with backend, systems, and product teams to ship new features and scale existing systems.

Must-Have

• Strong experience running infrastructure in production environments.

• Solid understanding of distributed systems, networking, and cloud architecture.

• Hands-on experience with Docker and Kubernetes.

• Experience with Infrastructure-as-Code tools such as Terraform or Pulumi.

• Experience with at least one major cloud provider (AWS, GCP, or Azure), including networking, compute, and security.

• Experience with observability tools such as Prometheus, Grafana, OpenTelemetry, or similar.

• Proficiency in Go, Rust, Python, or similar languages for tooling and automation.

• Strong troubleshooting skills and the ability to work through complex production issues.

• A track record of owning infrastructure projects end to end.

• Ability to collaborate effectively in a fast-paced, distributed engineering environment.

• Excellent communication skills in Business English, both spoken and written.

Levels we're hiring

• Principal: 10+ years - System design leadership, cross-team impact, mentorship, leading 5 Jr engineers in parallel and teams of at least 10 engineers

Bonus Points:

• Experience running AI or ML infrastructure, including model serving, GPU workloads, or inference platforms such as vLLM or Triton.

• Experience with API gateways, service meshes, load balancers, or rate limiting at scale.

• Experience with multi-region or multi-cloud deployments.

• Build the future of enterprise AI: Run the infrastructure that lets companies access and manage the world’s leading AI models through one unified platform.

• Solve meaningful technical challenges: Work on high availability, global scale, and low latency for production AI traffic.

• Work with emerging AI technologies: Operate infrastructure at the intersection of cloud, AI models, and enterprise workflows.

• Have a direct impact: Help shape the infrastructure of a growing platform where engineering decisions matter.

• Collaborate with an international team: Work alongside talented engineers and product builders across San Francisco and Latin America.

• Grow in a fast-moving environment: Take ownership, solve hard problems, and grow with the platform.