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Compa

engineering opportunity

Staff Software Engineer, Core Infrastructure

The engineer will own and lead infrastructure and DevOps projects across the company's products, systems, AI/ML, and data warehouse. Responsibilities include designing, building, and maintaining cloud infrastructure, improving CI/CD pipelines, and owning end-to-end reliability through monitoring and incident response.

Irvine, California, United StatesremoteFULL_TIME

Posted

About the role

What will you do at Compa?

About Compa

Compa is a venture-backed AI startup revolutionizing the future of compensation. In a dynamic job market with hiring challenges, accountability, and the rise of AI, companies need the best data to stay ahead of industry changes, competition, and costs. Compa has developed the premier real-time compensation data platform, delivering top-tier compensation intelligence to leading enterprise teams.

Compa is a compensation intelligence company built to augment enterprise compensation teams in the era of AI. Our customers include the world’s biggest companies: NVIDIA, Stripe, DoorDash, Open AI, TMobile, Moderna, Workday, Ulta, Target, and more. Locations: Compa headquarters are located in Irvine, California, with growing sites in Denver, Colorado and San Francisco, California.

We’re a collaborative, curious, and driven team that values transparency, ownership, and continuous learning and prioritizing in person work where possible.

The Role

As a Staff Software Engineer on the Core Infrastructure team at Compa, you will own and lead infra and platform engineering projects across Compa’s products, systems, AI/ML, and data warehouse.

In this role you will: Design, build, and maintain core infrastructure across cloud, data, and AI/ML systems Own and drive the evolution of Compa’s Kubernetes-based platforms that give engineers reliable environments Work on scaling and automation of infrastructure services and tooling Raise the bar on reliability and observability (SLIs/SLOs, monitoring, incident response) Design and improve CI/CD pipelines, deployment workflows, and infrastructure automation Drive major company initiatives like multi-cloud support and customer-managed encryption keys Lead platform engineering efforts that reduce toil and improve developer velocity Act as a technical leader and multiplier by setting direction and helping others level up Partner with leadership on what we build next and why

Minimum Qualifications

  • 8+ years of industry experience in a software engineering role working on infrastructure, platforms, or backend systems Deep, hands-on experience with managed Kubernetes platforms (e.g., EKS, GKE, AKS), including cluster architecture, networking, scaling, and upgrades Strong coding skills in Python, focused on building infrastructure and backend tooling Experience designing, building, and operating systems on multi-cloud infrastructure across AWS, GCP, and/or Azure Experience managing infrastructure across cloud boundaries, including identity, networking, data considerations, traffic routing, and failover strategies Deep understanding of networking, operating systems, cryptographic protocols and distributed systems fundamentals A passion for enabling teams to build fast while building safely through well-designed proactive detection mechanisms and tooling Comfortable in a startup: high ownership, fast pace, and ambiguity

Preferred Qualifications

  • Experience working with monitoring and observability tooling (e.g., Prometheus, Grafana, Datadog, OpenTelemetry) to operate systems at scale Strong understanding of DevOps + SRE practices (CI/CD, infrastructure as code, observability, incident response) Working knowledge of security principles (IAM, secrets, encryption, least privilege) Exposure to MLOps Experience working at early-stage startups

Which skills does this role require?

Cloud InfrastructureAutomationReliabilityPythonKubernetesNetworkingOperating SystemsCryptographic ProtocolsDistributed SystemsIaCML OpsSecurity Best PracticesSoftware EngineerCore InfrastructureAI StartupCompensation Data PlatformAI/MLData WarehouseScalingDeployment WorkflowsMulti-cloudEncryption KeysMetricsAlarmsDashboardsAWSGCPAzureMachine Learning

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