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Salary: USD 150,000 - 175,000 / annual
Newton Research is building AI agents that power media planning, buying, and measurement workflows for brands, agencies, and publishers. The company combines large language models and generative AI with domain expertise to create a closed-loop media lifecycle platform.
As Senior DevOps Engineer, you will own the Kubernetes platform end-to-end, from cluster architecture and workload design through developer experience. The product ships in two forms: a SaaS platform on AWS and customer-installed deployments on Azure and GCP. You'll design for portability from day one, ensuring workloads behave predictably across EKS, AKS, and GKE environments.
Key responsibilities include:
- Owning Kubernetes platform operations: cluster provisioning and lifecycle management (EKS primary; AKS and GKE for customers), upgrade strategy, autoscaling, node pool design, resource governance, and multi-tenancy boundaries
- Designing deployment workflows using Helm charts, GitOps (Argo CD, Flux), progressive delivery, and rollback strategies that work in customer-controlled environments
- Packaging and hardening applications for customer-installed Kubernetes, supporting installation and upgrades
- Managing in-cluster ecosystem: ingress, certificates, secrets management, service networking, and operators
- Building and maintaining cloud infrastructure in Terraform across AWS, Azure, and GCP
- Maintaining and improving CI/CD pipelines (GitHub Actions) from merge through production rollout
- Instrumenting systems with Prometheus, Grafana, OpenTelemetry, Sentry, and Better Stack; defining SLOs/SLIs and leading incident response
- Contributing to SSO integrations (SAML and OIDC) and customer onboarding
- Maintaining SOC 2 compliance: RBAC, admission control, pod security standards, image scanning, audit logging, encryption, and audit evidence collection
- Adopting and promoting AI tooling across engineering
Required qualifications: 7+ years in DevOps, SRE, platform, or infrastructure engineering with production system ownership at scale. Deep production Kubernetes experience including cluster operations, upgrades, autoscaling, RBAC, network policy, and workload debugging. Hands-on with Helm and GitOps deployment models. Strong Terraform experience across multiple clouds with deep AWS/EKS expertise and working knowledge of Azure and GCP. Proficiency with GitHub Actions or equivalent CI/CD. Experience with Prometheus, Grafana, and distributed tracing. SSO implementation via SAML 2.0 and/or OIDC with enterprise IdPs. SOC 2 or ISO 27001 support experience. Fluency in Python, Bash, or Go. Networking fundamentals and Linux system administration. Track record using AI as a practical daily tool. Ability to explain technical tradeoffs to non-technical stakeholders.
The company values engineers who understand Kubernetes deeply enough to know when it isn't the answer, who automate repeatable work, and who treat compliance as engineering discipline. You'll have significant autonomy over technical strategy and architecture, working directly with founders on hard technical problems with a modern stack.
