Senior Site Reliability Engineer – AI-focused

Oliver James; Dublin; Hybrid; EUR 83,000 - 148,000; Full time

Benefits offered by this job

Hybrid work model

Office in Dublin

Job summary

Oliver James seeks an AI-focused SRE to run, deploy and support AI workloads and internal platforms in a hybrid Dublin setting. You will ensure uptime, observability and resilience while collaborating with developers to build and operate AI tools and services across production and near-production environments.

The role emphasizes automation, incident response, and continuous improvement, with a strong focus on monitoring, metrics and deployment reliability in a FinTech‑adjacent environment.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 3-5 years’ experience in SRE/DevOps/Production Engineering.
• Experience with Splunk/Dynatrace in production environments.
• Experience CI/CD automation (Git/Bitbucket, Jenkins, Maven, Artifactory, Chef and/or XLR).
• Experience running or supporting AI/ML workloads.

Responsibilities

• Ensure services are reliable, observable and resilient.
• Support full lifecycle from design to deployment and improvements.
• Develop and improve Splunk/Dynatrace queries, dashboards and alerts.
• Collaborate with developers to deploy and operate AI tools and platforms.
• Improve CI/CD pipelines and deployment processes.

Skills

Splunk & Dynatrace

AI Workloads

CI/CD & DevOps

Python scripting

Shell scripting

Education

Bachelor's degree in Computer Science/Engineering/Math/Physics

Tools

Git/Bitbucket

Jenkins

Maven

Artifactory

Chef

XLR

Job description

• 12-month contract (potential to go permanent)
• Hybrid working model (with occasional shift work)
• Office location in Dublin
• Day-rate contract

• 12-month contract (potential to go permanent)
• Hybrid working model (with occasional shift work)
• Office location in Dublin
• Day-rate contract

Overview

We are looking for an AI-focused SRE professional centred on the running, deployment and operational support of AI workloads and internal platforms. You will work closely with developers to build, deploy and operate internal AI-enabled tools and services, while ensuring they remain reliable, observable and scalable across production and near-production environments.

As an SRE, you will be a steward of production, with a strong focus on uptime, observability, operational resilience and continuous improvement.

Top 3 Must-Have Requirements

• Splunk & Dynatrace Hands‑on experience with Splunk and Dynatrace, including monitoring, developing queries, creating alerts and supporting production environments.
• AI Workloads Experience running, deploying or supporting AI/ML workloads, preferably in production or near‑production environments.
• CI/CD & DevOps Automation Strong experience with CI/CD and deployment tooling, including Git/Bitbucket, Jenkins, Maven, Artifactory, Chef and/or XLR.

Key Responsibilities

• Act as a steward of production, ensuring services remain reliable, available, observable and operationally resilient.
• Support the full lifecycle of services from design and development through deployment, operation and continuous improvement.
• Monitor and maintain production and near‑production environments, focusing on uptime, observability and system health.
• Develop and improve Splunk and Dynatrace queries, dashboards, alerts and monitoring capabilities.
• Investigate production incidents and use observability data to identify root causes and improve reliability.
• Support the running and deployment of AI workloads and internal AI‑enabled services.
• Work closely with developers to develop, deploy and operate internal AI tools and platforms.
• Support and improve CI/CD pipelines and deployment processes.
• Run deployment plans using tools such as XLR and identify opportunities to improve reliability, efficiency and automation.
• Develop automation to reduce manual intervention and improve software delivery.
• Review operational and deployment processes and recommend improvements.
• Support services before launch through system design reviews, capacity planning and operational readiness assessments.
• Measure and monitor availability, latency, performance and overall system health.
• Scale systems sustainably through automation and engineering best practices.
• Analyse IT service management activities and provide feedback on operational gaps and resiliency concerns.
• Participate in incident response and blameless post‑incident reviews.
• Troubleshoot issues across the technology stack to reduce mean time to recovery (MTTR).
• Work collaboratively with development, operations and product teams.
• Share technical knowledge and mentor junior engineers.
• Collaborate with globally distributed teams across multiple locations and time zones.

Essential

Experience & Qualifications

• 3-5 years’ experience in SRE, DevOps, Production Engineering, Platform Engineering or a related discipline.
• Strong hands‑on experience with Splunk and Dynatrace, including monitoring, observability, queries and alerting in production environments
• Bachelor's degree in Computer Science, Engineering, Mathematics, Physics or a related technical discipline, or equivalent practical experience.
• Relevant cloud, DevOps, SRE or IT service management certifications are desirable.
• Strong experience with CI/CD and DevOps automation, including Git/Bitbucket, Jenkins, Maven, Artifactory, Chef and/or XLR.
• Experience supporting software deployments and production operations, with a focus on reliability, availability and incident response.
• Experience running, deploying or supporting AI/ML workloads, ideally in production or near‑production environments.
• Strong scripting/programming skills, ideally Python and Shell.
• Experience troubleshooting complex issues across the technology stack.
• Strong problem‑solving, communication and stakeholder management skills, with the ability to work effectively across development, operations and product teams.

Desirable

• Fintech or financial services experience, particularly within highly available, business‑critical environments.
• Experience with AI platforms, data platforms or large‑scale distributed systems.
• Experience with Apache NiFi and SQL.
• Additional programming experience with Java, C, C++, Go, Perl or Ruby.
• Experience mentoring engineers or providing technical leadership.

What Success Looks Like

Success will be measured through improvements in uptime, observability, deployment reliability, incident response and MTTR, alongside increased automation and reduced manual operational effort.

Key Notes

Role focus: SRE, Production Operations, AI Workloads and DevOps Automation

Core technologies: Splunk, Dynatrace, Git/Bitbucket, Jenkins, Maven, Artifactory, Chef, XLR

Industry: Fintech/Financial Services preferred