Top Remote Senior Level DevOps & Platform Engineering Jobs in CO

Support and maintain high-availability on-air broadcast, media, and streaming systems across on-prem and AWS. Lead incident response, troubleshooting, root-cause analysis, and vendor coordination. Build reusable infrastructure patterns, perform reliability improvements, upgrades, and preventive maintenance. Develop runbooks, operational standards, and mentor team members. Participate in a rotating 24/7 on-call schedule and occasionally support tier-1 events in person.

Build and operate cloud and on-premises network infrastructure supporting CrowdStrike’s global security platform. Responsibilities include developing Terraform modules, implementing AWS multi-region and hybrid networking architectures, supporting cloud migration and data center exit programs, contributing to architecture reviews, improving CI/CD and Kubernetes enablement, documenting standards, and monitoring infrastructure. The role requires cross-functional communication, compliance-aware design, infrastructure automation, and use of AI technologies to improve troubleshooting and operational efficiency.

Manage, maintain, and improve secure government cloud, hybrid, and multi-cloud infrastructure (Azure Gov/Azure GCC High, AWS GovCloud, GCP). Provide 24x7 operational support, incident/change management, advanced troubleshooting, compliance with FedRAMP/NIST/DISA/CIS standards, automation/IaC development, capacity and performance management, and technical guidance to improve architecture, security, and service delivery.

Implement and operationalize Managed Services for Government Cloud customers across Azure Government, Azure GCC High, AWS GovCloud or Google Assured Workloads. Design secure landing zones, automation, monitoring, governance, and operational runbooks; support onboarding, transitions, compliance (FedRAMP, NIST, CMMC, etc.), incident handling, and production handoff. Collaborate with architects, security, PMs, and Managed Operations; mentor junior engineers and contribute to standards and reusable automation.

Designs and owns Webflow’s foundational cloud and source-control infrastructure, including multi-account landing zones, networking, DNS, PKI, secrets, Infrastructure as Code, GitHub delivery pipelines, self-service hosting patterns, policy guardrails, observability, cost controls, and security baselines. Partners with SRE, security, and developer productivity teams to improve reliability, scalability, adoption, and performance while managing cloud vendors and tooling relationships.

Design, build, and operate cloud-native, enterprise-grade SaaS services on Azure. Lead architecture and design, develop APIs and UIs, apply AI-enabled engineering tools, ensure observability, support production incidents, and drive reliability, performance, and CI/CD improvements across teams.

As a Lead Infrastructure Engineer, you'll enhance database reliability, automate infrastructure, collaborate on initiatives, and participate in on-call duties.

The Lead Infrastructure Engineer will define and build infrastructure at Atticus, managing platforms, security, reliability, and empowering engineering teams.

Lead architecture and delivery of Control Center platform capabilities (MCP tool registries, AI orchestration, access automation). Design agentic AI integrations, HITL workflows, and evaluation/guardrail frameworks. Own backend services, SLOs, observability, incident response, and operational readiness for Tier-1 systems. Drive cross-team technical direction, author TDDs, run design reviews, mentor engineers, and partner with Product and Security to deliver secure, scalable platform primitives.

Work as an SRE embedded with product teams to improve reliability by fixing application code (primarily TypeScript), building observability (Prometheus, Loki, Grafana, Alloy), defining SLIs/SLOs, leading incident response and postmortems, automating toil, and supporting deployments across on‑prem DoD and AWS environments.

Design, build, and maintain high-throughput data ingestion and processing pipelines; integrate AI-powered infrastructure; implement and support complex computing algorithms and distributed services; own systems end-to-end including architecture, observability, reliability, and operational support; lead architectural initiatives and reduce system complexity while maintaining performance on large-scale real-time data.