DevOps Engineer

Inframark

1d•Remote

About The Position

Step into the future with Inframark's award-winning Automation and Intelligence team. We deliver cutting-edge solutions in instrumentation and controls, industrial cybersecurity, data analysis, and remote network operations center services for water and wastewater plants. Elevate your career and join us at Inframark. Apply today! Why Work for Inframark? Our dedication to sustainability and community impact drives us to ensure clean, safe water for future generations. Whether you're at the start of your career or looking for advancement, Inframark offers purpose-driven work and opportunities for growth. We offer an attractive salary package, including a generous benefits package with health, dental, and life insurance, 401(k) plan, paid time off, sick leave, holidays, and wellness plan. We're looking for a DevOps Engineer who takes ownership of infrastructure. You'll stabilize and modernize the infrastructure supporting WaterMinds, our cloud-based platform for water and wastewater utilities—implementing proper monitoring and alerting, upgrading production environments, establishing operational discipline, and enabling our engineering teams to ship with confidence. You'll follow DevOps best practices, proactively identify and solve problems, and drive infrastructure improvements with minimal direction. The challenge: build and maintain infrastructure that can reliably serve hundreds of utility customers at scale. Your immediate focus is moving our infrastructure from reactive firefighting to proactive maintenance mode. As the platform matures and our data science team ramps up, you'll have the opportunity to transition into MLOps, building the infrastructure that enables machine learning at scale.

Requirements

5+ years of experience in DevOps, infrastructure, or site reliability engineering.
Demonstrated ability to take ownership and initiative—you see what needs to be done and do it without waiting for direction.
Deep knowledge of DevOps and infrastructure best practices—you know what good looks like and implement it proactively.
Strong Kubernetes experience (EKS preferred) including cluster management, deployments, services, and troubleshooting.
Hands-on AWS experience (EC2, EKS, ECS, RDS, VPC, IAM, CloudWatch, S3).
Infrastructure as code proficiency (Terraform and Ansible).
GitOps experience (ArgoCD, Flux, or similar).
CI/CD pipeline experience (Bitbucket Pipelines, Jenkins, GitHub Actions, or similar).
Monitoring and observability experience (Prometheus and Grafana preferred).
Python scripting ability for automation and tooling.
US citizenship (required for AWS GovCloud access).
Self-starter mentality—you identify problems and opportunities, then drive solutions to completion.
Proven track record of delivering tested, high-quality infrastructure changes on schedule.
Excellent communication skills—proactive about sharing status, raising blockers, and documenting decisions.

Nice To Haves

Curiosity about machine learning and interest in transitioning to MLOps as the platform matures.
Any MLOps or ML infrastructure experience (KServe, Kubeflow, SageMaker, model serving).
Experience with data pipelines, feature engineering, or supporting data science teams.
AWS GovCloud experience and understanding of compliance requirements (FedRAMP).
Experience with message queue systems (Kafka, Redpanda).
Container security and vulnerability scanning (Snyk).
Background in SaaS platforms, IoT, or critical infrastructure.

Responsibilities

Take ownership of production monitoring and alerting using Prometheus, Grafana, and CloudWatch—proactively identify issues before they become incidents.
Modernize production EKS cluster with GitOps practices (ArgoCD), comprehensive monitoring, and proper deployment workflows following industry best practices.
Streamline staging deployment process; eliminate branch-based workarounds and establish clean GitOps patterns.
Design infrastructure patterns that scale to hundreds of customers and own AWS infrastructure operations including patching, maintenance, cost optimization, and security compliance—stay ahead of requirements.
Expand into MLOps—building the infrastructure that enables data scientists to deploy models at scale across multiple utility customers once DevOps operations are automated.
Manage Kubernetes clusters (EKS) including pod migrations, resource optimization, troubleshooting, and security updates—proactively, not reactively.
Maintain infrastructure as code using Terraform and Ansible following best practices—all changes tested in non-production before deployment.
Support engineering teams with infrastructure needs, unblock them quickly, and establish self-service patterns where possible—anticipate needs, don't wait for requests.
Manage message queue infrastructure (Kafka/Redpanda) including retention policies, storage optimization, and performance tuning.
Document infrastructure, create runbooks, and automate operational tasks to move systems into maintenance mode.
Clean up technical debt—proactively identify infrastructure to decommission, resources to consolidate, and costs to optimize.