AI Platform Cloud Infrastructure Engineer

Epiq Systems, Inc; United States; Remote; USD 180,000 - 260,000; Full time

Job summary

Epiq AI Labs is seeking a senior infrastructure engineer to design, build, and operate the cloud infrastructure and automation behind our AI platform. You will manage infrastructure as code, Kubernetes, CI/CD, networking, secrets, and observability across Azure, AWS, and Epiq-managed on‑prem GPU environments.

You will own design through production, collaborate with backend AI engineering, product management, and security to establish scalable deployment, observability, and security patterns.

Qualifications

• 3+ years of professional experience in infrastructure engineering, platform engineering, or site reliability engineering.
• Hands-on experience with at least one major cloud platform such as AWS, GCP, or Azure.
• Experience with infrastructure-as-code tools, particularly Terraform, including reusable module design.
• Production Kubernetes experience, including scaling, upgrades, resource limits, network policy, and troubleshooting.
• Ownership of CI/CD pipelines using GitHub Actions, Azure DevOps, or a comparable platform.
• Experience using observability tools such as Prometheus, Grafana, or OpenTelemetry to monitor service health, diagnose incidents, and track service-level objectives.
• Experience participating in production incident response and applying lessons from incident reviews.
• Experience managing secrets and certificates in production, including secure storage, rotation, and renewal.
• Proficiency in Python, Go, or a comparable language, with experience building, testing, and maintaining production tooling and automation.
• Demonstrated proficiency using AI coding agents in day-to-day development, with sound judgment about where they accelerate and where they fail.
• Senior+ level: Demonstrated technical leadership and ability to lead technical direction across organizational boundaries.
• Senior+ level: Strong emphasis on reliability, capacity planning, and incident management at scale.

Responsibilities

• Write, test, review, and maintain reusable Terraform modules and infrastructure automation for provisioning, environment configuration, and drift detection and remediation.
• Operate Kubernetes in production, including orchestration, autoscaling, resource governance, network policy, and cluster lifecycle management.
• Build and maintain CI/CD and GitOps release automation, improving build and test feedback and targeting zero-downtime rollouts.
• Operate the Epiq-managed GPU infrastructure (cloud and on-prem) that serves Epiq AI's in-house models: cluster management and scheduling, utilization and cost, observability, and model-serving reliability.
• Define platform service-level objectives and build the metrics, tracing, alerting, and error-budget practices required to support them.
• Implement security and compliance infrastructure, including hardening, audit logging, data-residency controls, retention, legal hold, and audit evidence collection.
• Build and maintain network, secrets, key, credential, TLS, and certificate-lifecycle infrastructure.
• Use AI coding agents throughout development while owning the outcome and ship major changes behind automated tests and controlled rollouts.
• Build and maintain AI-native developer tooling and technical design documentation, and contribute to architectural reviews.
• Participate in the on-call rotation and incident response; maintain runbooks, test backup and restore procedures, and turn incident findings into lasting fixes.
• Senior+ level: Define foundational infra architecture and patterns and lead major migrations, modernization, and capacity planning.

Skills

Python

Go

Terraform

Kubernetes

CI/CD

GitHub Actions

Azure DevOps

Prometheus/Grafana/OpenTelemetry

Tools

Terraform

Kubernetes

CI/CD pipelines

Prometheus

Grafana

OpenTelemetry

PostgreSQL

Job description

Epiq AI Labs is seeking a senior infrastructure engineer to design, build, and operate the cloud infrastructure and automation behind our AI platform. You will manage infrastructure as code, Kubernetes, CI/CD, networking, secrets, and observability across Azure, AWS, and Epiq-managed on‑prem GPU environments.

You will own design through production, collaborate with backend AI engineering, product management, and security to establish scalable deployment, observability, and security patterns.