> Markdown version of [/jobs/ext/3992091-devops-sre-engineer-only-w2](https://www.wearedevelopers.com/jobs/ext/3992091-devops-sre-engineer-only-w2). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # DevOps / SRE Engineer (Only W2) - **Company:** Trispark Inc - **Location:** Virginia Beach, VA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Adobe InDesign, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Audit Trail, BigQuery, Cloud Computing, Continuous Integration, Software Debugging, Linux, DevOps, Domain Name System (DNS), Github, Identity and Access Management, Virtual Private Networks (VPN), Peering, Prometheus, Data Logging, Network Switches, Google Cloud, Cloud Platform System, Data Ingestion, Cloud Monitoring, Autoscaling, Delivery Pipeline, Grafana, Multi-Cloud, Build Server, Amazon Virtual Private Cloud (VPC), Git, Kubernetes, Data Management, Cloudwatch, Terraform - **Published:** October 28, 2026 - **Apply:** https://www.dice.com/job-detail/2f39b29d-3cb6-4f9e-9163-c249ae362d26 ## About the Role 4-5 years in DevOps, SRE, or platform engineering. - Strong hands-on Kubernetes experience in production (GKE and/or EKS) - scheduling, resources, networking, troubleshooting. - Multi-cloud experience - production work on both Google Cloud Platform and AWS (or deep in one with solid working knowledge of the other). - Solid Terraform experience - modules, state, reviews, and safe apply workflows you have used in production. - Working knowledge of CI/CD (GitHub Actions, Cloud Build, CodePipeline, or similar) for infra and containerized apps. - Comfortable with Linux, containers, and debugging production issues from logs/metrics. - Cloud fundamentals across providers: IAM, VPC/networking, managed Kubernetes, secrets, monitoring/logging. - Clear written communication - runbooks, PR descriptions, incident notes. Preferred Qualifications - Airflow on Kubernetes / GKE operations. - Helm / Kustomize for app and platform packaging. - Prometheus, Grafana, Cloud Monitoring, and/or CloudWatch at scale. - Experience with Spot/preemptible node pools and cost-aware capacity planning across clouds. - Prior work in SOC 2 or similarly controlled environments. - Exposure to data platforms (BigQuery, dbt, ingestion pipelines) as a platform consumer. ## Description Data and AI platform company building managed data products for federal and enterprise clients. Our stack is multi-cloud - primarily Google Cloud Platform (GKE, BigQuery, Cloud Monitoring) with AWS workloads and cross-cloud networking - orchestrated via Terraform, Kubernetes, and CI/CD (GitHub Actions). We're hardening platform reliability and operations as part of a broader push toward SOC 2 compliance. The Opportunity We're scaling a multi-cloud, multi-cluster Kubernetes platform that runs data ingestion, orchestration (Airflow), search (Vespa), and API workloads across Google Cloud Platform and AWS. Much of the infrastructure exists as Terraform and Helm, but reliability, observability, and operational maturity still need ownership - from networking and node-pool design through incident response and CI/CD hardening. You will own the reliability and operability of our Kubernetes and cloud platform: keep clusters healthy across clouds, make deployments safe and repeatable, and turn tribal ops knowledge into runbooks and alerts. This is a hands-on build role with strong mentorship and direct exposure to architecture decisions. What You'll Do - Own day-to-day reliability of Kubernetes clusters (GKE / EKS): node pools (Spot/standard), autoscaling, taints/labels, and workload placement. - Maintain and extend Terraform modules for VPC, clusters, IAM, and add-ons across Google Cloud Platform and AWS; land all infra changes through Git and PRs. - Design and operate cross-cloud networking and connectivity (VPC, peering, VPN/Interconnect, DNS, private service access). - Operate and improve Airflow-on-Kubernetes (executor configs, resource requests, pod scheduling, and failure recovery). - Build and harden CI/CD (GitHub Actions) for infra and app deployments - gated promotes, environment isolation, rollback paths. - Design observability: metrics, logs, traces, SLOs/SLIs, and actionable alerting across clouds (not alert noise). - Write runbooks for common failure modes; lead or support incident response and postmortems. - Harden security posture for SOC 2: least-privilege IAM, secret management, audit logging, change control. - Partner with data and platform engineers on capacity, cost, and performance trade-offs. - Participate in design discussions, surface trade-offs, and propose improvements as you encounter them in the stack.