Senior Specialist - Platform Reliability and Application Support

Role overview

Core responsibilities

• Understand assigned services, user journeys, application components, data flows, runtime behavior, and third-party dependencies.
• Implement service-level indicators and reliability objectives covering availability, latency, and successful processing.
• Improve logs, metrics, traces, dashboards, and alerting to identify customer impact and failures.
• Diagnose production issues across code, APIs, queues, databases, containers, and underlying services.
• Read code and trace failures; deliver tested automation, diagnostic tooling, and reliability improvements.
• Coordinate incident recovery and communicate impact, evidence, mitigation, and recovery confidence.
• Work with customers and internal users during complex investigations and align communications with Application Support.
• Improve deployment readiness, health checks, staged rollouts, recovery mechanisms, and rollback criteria.
• Test performance, resilience, dependency failures, capacity limits, and service recovery.
• Use incident reviews and reliability trends to prioritize improvements and reduce repetitive manual work.
• Maintain runbooks, secure access, handovers, shared knowledge, and verified corrective actions.
• Participate in the agreed production on-call rota, incident response, maintenance, and recovery exercises.

Required qualifications

• Strong production application support or reliability engineering experience with software products and complex incidents.
• Ability to debug application code in a relevant language such as Python, Java, C#, Go, or JavaScript/TypeScript.
• Ability to write maintainable automation, use Git, review changes, and test before production use.
• Practical experience with observability, distributed tracing, alerting, and service health measures.
• Working knowledge of Linux, containers, cloud services, APIs, databases, and networking.
• Experience with CI/CD, production change validation, incident response, and recovery; attention to access controls and customer data.
• Strong communication and independent problem-solving skills, with evidence of reducing recurring failures or operational effort.

Preferred experience

• Kubernetes or OpenShift, Azure, infrastructure as code, or open observability tooling.
• Service-level objectives, error-budget practices, load testing, or resilience exercises.
• AI inference or data-processing platforms, including dependencies, queue behavior, and capacity constraints.

Success measures

What the company offers

• The company describes an open, diverse, inclusive environment, learning and development opportunities, structured training, and high-tech projects.
• A competitive remuneration package with healthcare, education support, and leave benefits is described.