Site Reliability & DevOps Engineer (Mid-Level) -Splunk, PagerDuty

Nextiya LLC; Fairfax (VA); On-site; USD 90,000 - 130,000; Full time

Job summary

Nextiya LLC is seeking a hands-on Site Reliability & DevOps Engineer (Mid-Level) to support production infrastructure, monitoring pipelines, and incident workflows in Fairfax, VA. The role involves log aggregation, proactive alert tuning, cloud automation, and integrating AI-assisted developer tooling into daily operations.

The ideal candidate has 3–6 years in DevOps/SRE, strong pagerduty and Splunk skills, and experience with Terraform, Ansible, and Docker in a hybrid/cloud setting.

Qualifications

• 3–6 years of experience in DevOps, SRE, or Systems Administration.
• Incident Management: proficient with PagerDuty and incident lifecycle handling.
• Observability: strong Splunk knowledge (SPL queries, dashboards, log forwarders).
• Automation & CI/CD: hands-on with Terraform, Ansible, and Docker-based environments.
• Scripting Skills: Python or Shell scripting for automation.
• OS: strong Linux administration and troubleshooting.

Responsibilities

• Incident Response & Reliability: support on-call operations and incident lifecycle management.
• Observability & Log Analytics: maintain centralized logs, dashboards, and alerts across hybrid environments.
• Infrastructure Automation: write IaC with Terraform and Ansible for containerized and virtualized infra (Docker, Proxmox/KVM, AWS).
• Scripting & Tooling: develop automation scripts and internal API integrations.
• AI Tooling Adoption: leverage AI tooling to accelerate workflows and automation.

Skills

Incident management

Observability

Automation & CI/CD

Scripting

Linux administration

Tools

PagerDuty

Splunk

Terraform

Ansible

Docker

AWS

Zabbix

Rundeck

Proxmox

rsyslog

Ollama

vLLM

Job description

Site Reliability & DevOps Engineer (Mid-Level) -Splunk, PagerDuty

Fairfax, United States | Posted on 09/28/2026

We are seeking a hands-on Site Reliability & DevOps Engineer to support, automate, and optimize our production infrastructure, monitoring pipelines, and incident management workflows. In this role, you will help manage log aggregation, tune proactive alerting, automate cloud infrastructure, and assist in integrating AI-assisted developer tooling into our daily operational workflows.

Key Responsibilities

Incident Response & Reliability: Support on-call operations and incident lifecycle management using PagerDuty and Rundeck to streamline response times and reduce Mean Time to Resolution (MTTR).

Observability & Log Analytics: Maintain centralized log aggregation, dashboards, and alerting rules across hybrid environments using Splunk and network monitoring tools (e.g., Zabbix, rsyslog).

Infrastructure Automation: Write and maintain Infrastructure as Code (IaC) using Terraform and Ansible to manage containerized and virtualized environments (Docker, Proxmox/KVM, AWS).

Scripting & Tooling: Develop custom automation scripts, internal API integrations, and maintenance tooling using Python , Bash/Shell , or Go .

AI Tooling Adoption: Utilize modern AI development tools (e.g., Claude Code, GitHub Copilot, local LLM endpoints) to accelerate internal engineering workflows and assist with operational automation.

Requirements

Required Qualifications

3–6 years of experience in DevOps, Site Reliability Engineering (SRE), or Systems Administration.

Incident Management: Strong hands-on experience setting up and managing services, schedules, and escalation policies in PagerDuty .

Observability: Solid working knowledge of Splunk (writing SPL queries, creating dashboards, configuring log forwarders) and core telemetry tools.

Automation & CI/CD: Practical experience with Terraform , Ansible , and containerization via Docker .

Scripting Skills: Proficiency in Python or Shell scripting for day-to-day task automation.

Operating Systems: Strong proficiency with Linux administration and troubleshooting.

Nice-to-Have Skills

Experience with automated runbook tools like Rundeck .

Exposure to AI-assisted coding/ops workflows (e.g., Ollama, vLLM, or Model Context Protocol integrations).

Background in virtualized infrastructure (Proxmox, Xen, ESX) or cloud platforms (AWS).