SRE

Infinity Quest
UK
2 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
£48,103.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Distributed Systems Information Technology Operations Python (Programming Language) Machine Learning Reliability Engineering Ansible Datadog Mttr Containerization
+3 more
Dynatrace Docker Microservices

Job description

  • Work closely with Product Engineering team and implement strategies for modernizing IT operations enhancing observability and toil reduction.
  • Architect and deploy observability platforms to monitor system health, performance, and reliability effectively.
  • Propose & drive strategies for AI-driven alerting and proactive anomaly detection to reduce MTTD & MTTR.
  • Develop and enforce SRE best practices, including Service Level Objectives (SLOs), Service Level Indicators (SLIs), and Error Budgets.
  • Establish & create AIOPS roadmap for improving operational efficiency.
  • Lead efforts to automate repetitive tasks (toil) using scripting, orchestration tools, and AI/ML-based solutions.
  • Drive toil automation initiatives for automated incident responses & self-healing automation for achieving autonomous operations.
  • Collaborate with cross-functional teams to ensure systems are scalable, resilient, and maintainable.
  • Drive incident management and root cause analysis processes through automation, ensuring continuous improvement to enable autonomous operations.
  • Partner with engineering, architecture, and product teams to enable shift-left engineering practices ensuring reliability.
  • Mentor and guide teams on adopting SRE principles and tools.
  • Advocate for a culture of reliability, automation, and continuous improvement across the organization.

Requirements

  • Strong expertise in implementing Site Reliability Engineering (SRE) principles.
  • Advanced knowledge of establishing observability using tools Dynatrace & Datadog (primary skills).
  • Proficiency in automation & scripting using Python & Ansible (primary skills).
  • Strong experience with cloud platforms AWS & Azure (primary skills).
  • Solid understanding of containerization and orchestration tools like Docker and Kubernetes.
  • Proficiency in cloud native distributed systems & microservices architecture.

  • Exposure to AI/ML techniques for predictive analytics and automated problem resolution.
  • Familiarity with CI/CD pipelines & enabling automated release & deployment engineering solutions.
  • Good to have experience with chaos engineering tools like Gremlin or Chaos Monkey and implementing automation frameworks for resilience tracking.
  • Ability to manage and prioritize multiple projects in a fast-paced environment.
  • Strong interpersonal and communication skills to work effectively across teams.
  • Excellent problem solving, analytical thinking, and adaptability.

Strategic mindset balancing engineering excellence with business priorities.

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