Site Reliability Engineer

Aquent is proud to partner with a leading innovator within the financial services industry, a company dedicated to empowering millions of individuals and institutions to achieve their financial goals. In this dynamic role, you will have a direct, tangible impact on the stability, performance, and scalability of mission-critical systems that serve millions of clients daily. By driving automation and operational excellence across both on-premises and cutting-edge cloud platforms, you will help shape the future of a highly secure and rapidly evolving financial ecosystem.

The Opportunity

We are seeking a highly motivated reliability professional with an automation-first mindset to join a pivotal team dedicated to elevating production systems. You will thrive on solving complex challenges, eliminating manual operational effort, and ensuring seamless service delivery. This is an exciting opportunity to collaborate with talented engineers, leverage emerging AIOps and observability technologies, and continuously improve system resilience at an enterprise scale.

What You'll Do

• Develop robust Python-based automation solutions to significantly reduce manual operational effort and enhance efficiency across diverse environments.
• Automate infrastructure management across Linux, Windows, Kubernetes, and cloud-native environments to build scalable, resilient systems.
• Integrate various tools and platforms through APIs and client libraries to streamline workflows and improve system interoperability.
• Support CI/CD automation and deployment reliability initiatives to ensure smooth, consistent, and secure software releases.
• Monitor and maintain production systems to consistently meet and exceed reliability and availability objectives.
• Actively participate in incident response, thorough troubleshooting, and root cause analysis (RCA) to prevent recurrence and enhance system stability.
• Develop proactive automation and operational improvements to eliminate recurring issues and elevate system resilience.
• Support disaster recovery, failover testing, and other operational readiness activities to ensure business continuity.
• Perform in-depth performance analysis and regular system health reviews to optimize system behavior.
• Build and maintain comprehensive dashboards, alerts, and monitoring solutions using Splunk, Grafana, Prometheus, or similar industry-leading tools.
• Improve visibility into application and infrastructure health through enhanced metrics, logs, and traces for proactive issue detection.
• Explore AI/ML-driven operational improvements, such as anomaly detection, intelligent alerting, and log analytics, to advance predictive insights.

What You'll Bring

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 3 to 5 years of hands-on experience in production operations, reliability engineering, DevOps, or platform engineering.
• Proven experience supporting large-scale production systems, with a deep understanding of operational challenges in enterprise environments.
• Strong programming skills in Python as a primary language for automation and tooling development (beyond basic scripting).
• Demonstrated experience building automation tools, scripts, frameworks, or operational solutions.
• Experience supporting Kubernetes and major cloud platforms (such as GCP, AWS, or Azure).
• Familiarity with infrastructure automation and configuration management tools.
• Experience with monitoring and observability platforms like Splunk, Grafana, Prometheus, or Datadog.
• Solid understanding of Linux systems, networking concepts, and distributed applications.
• Strong analytical, troubleshooting, and problem-solving skills, with experience in critical production incident management.

What Will Set You Apart

• Experience with Infrastructure as Code (IaC) solutions such as Terraform or Ansible.
• Exposure to OpenTelemetry and modern observability practices.
• Experience with CI/CD pipelines and deployment automation.
• Knowledge of AI/ML, AIOps, or intelligent operational tooling.
• Experience supporting highly available production systems in regulated or enterprise environments.