Site Reliability Engineer

Axle•Frederick, MD

12d•$140,000 - $155,000

About The Position

The Site Reliability Engineer role centers on modernizing and consolidating a complex multi-cloud environment across AWS, Azure, and GCP, building a scalable, secure, and observable platform from the ground up using Kubernetes, AI/ML infrastructure, and zero-trust principles. You'll combine DevOps and SRE practices to support mission-driven scientific and clinical programs, emphasizing automation, reliability, compliance, and proactive monitoring while enabling innovation through AI-driven tooling. The team culture is highly collaborative and growth-oriented, valuing experimentation, continuous learning, and cross-functional leadership, with opportunities to shape future multi-cloud and platform engineering solutions.

Requirements

Must have total of 6+ experience DevOps / SRE roles with monitoring and observability tools (Prometheus, Grafana, ELK, or cloud-native equivalents) for on-prem and cloud hosted workloads.
Must have 4+ years of Hands-on Linux experience that includes Ubuntu/CentOS/Red Hat operating systems, containers, dependency management and administration support
Must have 4+ years of experience automating Infrastructure-as-Code (IaC) deployments to one of the following cloud platforms Amazon AWS, Google GCP and Microsoft Azure
Must have 4+ years with CI/CD and automation tools such as Terraform, Ansible, Chef, Puppet, Jenkins, GitHub Actions
Strong scripting skills (Python, Bash, PowerShell or similar)
Must be proficient using vibe coding and coding assistants to develop scripts, tools and applications for the DevOps and SRE use cases
Must have proficiency to debug or troubleshoot and/or deploying SQL and/or NoSQL databases, object storage, web servers, open-source programming stack for Node.JS, R, Python, .NET Core, Java is desired but not mandatory
Must be willing to learn new technologies, adopt and adapt to emerging technologies or needs from a project to a project

Nice To Haves

Cloud certifications is preferred
Certifications in Grafana, Splunk, Docker, Kubernetes is preferred but optional

Responsibilities

Design and implement enterprise-grade monitoring and observability frameworks (metrics, logs, traces) across distributed systems using enterprise Splunk, Grafana and Open-telemetry tools
Establish and manage SLIs, SLOs, and error budgets to drive reliability improvements
Develop and maintain real-time asset inventory systems across cloud, on-prem, and hybrid environments
Automate workload onboarding and offboarding processes, ensuring standardization and governance
Track system ownership, dependencies, and lifecycle states for operational transparency
Build proactive detection mechanisms using AIOps and intelligent alerting to minimize incident impact
Design and operate scalable, resilient, and secure infrastructure platforms across cloud and hybrid environments
Implement automated compliance tracking and enforcement aligned with organizational and regulatory standards (e.g., NIST, FISMA, FedRAMP)
Embed ITIL processes (incident, change, problem, configuration management) into SRE workflows
Build and maintain automated deployment environments and pipelines that enforce security, compliance, and operational standards
Develop “golden paths” and standardized platform templates for consistent workload deployment
Automate provisioning, patching, configuration management, and environment lifecycle
Leverage AI/ML coding assistants and vibe coding practices to rapidly develop automation scripts, tools, and internal platforms
Integrate AI-driven tooling into DevOps pipelines for code quality, security scanning, and operational insights
Lead adoption of AI-enhanced SRE practices, including intelligent remediation and predictive operations
Champion DevOps and SRE practices including Infrastructure as Code, CI/CD, observability, and reliability engineering
Build developer-friendly platforms (“golden paths”) that simplify deployments, reduce friction, and improve velocity
Enable and optimize infrastructure for AI/ML workloads, including data pipelines, storage systems, and inference environments, GPU-enabled and high-performance compute workloads
Build and manage containerized and orchestrated platforms (Docker, Kubernetes)
Support cloud migration, modernization, and platform standardization initiatives
Ensure systems meet security, compliance, backup, and disaster recovery requirements
Evangelize and promote best practices in DevOps, SRE, and platform engineering to developer communities
Stay abreast of new technologies in your areas but not limited to AIOps, MLOps, cloud computing & deployment, site reliability engineering, infrastructure automation, security best practices, data engineering etc.