Senior Site Reliability Engineer

Spectraforce Technologies; Austin (TX); Hybrid; USD 130,000 - 170,000; Full time

Job summary

Spectraforce Technologies in Austin, TX is seeking a Senior Site Reliability Engineer to design and implement scalable, automated operations for complex enterprise systems. You will advance AI/ML‑driven observability and reduce toil across cloud and on‑prem environments.

This role emphasizes scripting, CI/CD automation, incident response, capacity planning, and collaboration with engineering teams. Ideal candidates have 6–8 years of enterprise IT experience, strong Linux/Windows administration,

Qualifications

• 6-8 years of enterprise-level administration and support

Responsibilities

• Evangelize SRE mindset and solve problems through systematization
• Identify opportunities to build innovative tools and solve operations problems on large enterprise and mission-critical applications
• Create scripts to automate operational tasks and incorporate solutions into infrastructure; architect and own production automation solutions
• Design and implement AI/ML-driven automation pipelines, observability enhancements, and proactive operational response systems
• Lead expansion of automation coverage across deployment, monitoring, alerting, and self-healing workflows for Cloud and Login Platforms
• Collaborate with Engineering, Scrum, and Ops resources to provide technical expertise and support on key initiatives for system availability and reliability
• Triage alerts and diagnose/resolve critical issues; manage implementation of changes with minimal risk
• Develop tools, frameworks, and instrumentation to validate and increase rollout success for applications; leverage AI/ML capabilities to enhance operational visibility
• Champion AIOps platform adoption and ML-assisted observability practices across the team
• Coordinate capacity planning using data-driven trend analysis and ML-informed forecasting
• Develop CI/CD orchestration systems to reduce friction for software delivery to production; drive adoption of GitOps and AI-assisted pipeline optimization
• Real-time troubleshooting of mission-critical application workflows and incorporate feedback into product development
• Participate in on-call support

Skills

Automation scripting

Monitoring dashboards

SDLC

Linux administration

Windows administration

Cloud configuration

Networking

Distributed systems

Programming: .NET/PowerShell/Java

Observability tools

AIOps/AI/ML

Education

Bachelor's degree in Computer Science

Tools

Splunk

AppDynamics

Kubernetes

GitHub Actions

Jenkins

Kafka

RabbitMQ

IBM MQ

Solace

GCP

Job description

Title: Senior Site Reliability Engineer

Duration: 06 Months

Location: Austin, TX - Hybrid 4 days weekly onsite

Our Opportunity

We are looking for a skilled engineer with disciplines that incorporate aspects of software systems engineering and operations. We are combining these skills to come up with better ways of managing and operating applications - including AI/ML-driven approaches to observability and reliability.

What you'll do

• Evangelize SRE mindset and solve problems through systematization.
• Identify opportunities to build innovative tools and solve unique operations problems on large enterprise and mission-critical applications.
• Create scripts to automate operational tasks and incorporate solutions into infrastructure; architect and own production automation solutions that measurably reduce manual toil and improve operational throughput.
• Design and implement AI/ML-driven automation pipelines, observability enhancements, and proactive operational response systems - including anomaly detection and predictive alerting to improve platform reliability.
• Lead expansion of automation coverage across deployment, monitoring, alerting, and self-healing workflows for Cloud and Login Platforms.
• Collaborate with Engineering, Scrum, and Ops resources to provide technical expertise and support on key initiatives for system availability and reliability.
• Triage alerts and diagnose/resolve critical issues; manage implementation of changes with clear communication and minimal risk.
• Develop tools, frameworks, and instrumentation to validate and increase rollout success for applications; leverage AI/ML capabilities to enhance operational visibility and rollout validation at scale.
• Champion AIOps platform adoption and ML-assisted observability practices across the team.
• Coordinate capacity planning using data-driven trend analysis and ML-informed forecasting.
• Develop CI/CD orchestration systems to reduce friction for software delivery to production; drive adoption of GitOps concepts and AI-assisted pipeline optimization.
• Real-time troubleshooting of mission-critical application workflows and incorporate feedback into product development.
• Participate in on-call support.

Required Skills

• 6-8 years of experience with enterprise-level administration and support.
• 6-8 years of experience writing automation scripts, building application dashboards for proactive monitoring, and setting up alerts for early issue determination.
• 6-8 years practicing SDLC, process improvements.
• Hands-on enterprise systems administration, monitoring, and deployment activities.
• Experience with Windows 2019/2022 and Linux hosted via Virtual Machine.
• Experience in Cloud application configuration, deployment, support, and migration - GCP/PCF is a plus.
• Knowledge of IP networking including DNS, DHCP, firewalls, IP routing, etc.
• Familiarity with large-scale distributed systems and high-availability architecture.
• Linux and Windows system administration, troubleshooting, and tuning.
• Development experience in one or more programming languages: .NET, PowerShell, Java, Python, Bash.
• Knowledge of one or more of SQL, Oracle, MongoDB databases.
• Working knowledge of Actimize.
• Knowledge of one or more Message Brokers: Solace, RabbitMQ, IBM MQ, Kafka.
• Knowledge of Splunk, AppDynamics, or similar observability tools.
• Demonstrated experience applying AI/ML or AIOps approaches (e.g., anomaly detection, predictive alerting, ML-assisted observability) in production environments.
• Bachelor's degree in computer science or related discipline.

Helpful Skills

• Financial services industry experience.
• Agile methodologies.
• Hands-on experience with AIOps platforms or ML-driven observability tooling.
• Experience integrating AI/ML capabilities into CI/CD or operational automation workflows.
• Familiarity with CI/CD tools (Harness, Jenkins, GitHub Actions) or GitOps concepts.
• Exposure to container orchestration (Kubernetes, OpenShift) or cloud platforms (AWS, Azure, GCP).

Personal Skills

• Strong customer orientation with an affinity to proactively own, communicate, and follow through on projects and issues.
• Extreme sense of ownership to resolve problems in a distributed environment.
• Gritty resolve to dig deeper into technical issues in a complex login ecosystem.
• A self-starter with the ability and confidence to independently resolve issues and bring results back to the team.