Senior Specialist - Platform Reliability and Application Support (Inception42)

Inception42, a G42 company, is the region\u2019s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer \u2013 transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inception42.ai Inception42, a G42 company, is the region\u2019s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception42 functions as the core intelligence layer \u2013 transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception42 is committed to creating positive societal impact. For more information, please visit www.inceptionai.ai Improve the production reliability of the platforms, products and applications developed by Inception42 for internal users and external customers. You will combine application support experience with engineering to detect problems early, restore service effectively and prevent recurrence. This is a senior individual contributor role focused on application and service reliability. You will investigate across code and runtime dependencies, build useful operational tooling and work closely with Product Engineering to make services easier to operate and recover. Works within Tech Services alongside platform leadership, Product Engineering, Application Support, Azure Cloud, NetSecOps and Information Security. Partners with Application Support on customer cases and communicates directly with internal users and external customers during technical investigations and incidents. \u2022 Understand assigned services end to end, including user journeys, application components, data flows, runtime behaviour and third-party dependencies. \u2022 Implement service level indicators and agreed reliability objectives with service owners, covering user-relevant availability, latency and successful processing. \u2022 Build and improve logs, metrics, traces, dashboards and alerting so operational teams can identify customer impact and locate failures quickly. \u2022 Diagnose production issues across application code, APIs, queues, databases, containers and underlying services, working with domain engineers where needed. \u2022 Read source code and trace execution paths to explain failures; write tested automation, diagnostic tooling and reviewed reliability improvements. \u2022 Respond to incidents, coordinate technical recovery for assigned services and provide clear updates on impact, evidence, mitigation and recovery confidence. \u2022 Work directly with customers and internal users during complex investigations, explaining findings in accessible language and keeping communication aligned with Application Support. \u2022 Improve deployment readiness, health checks and recovery mechanisms with Engineering. Validate changes through staged rollout, operational checks and agreed rollback criteria. \u2022 Identify capacity limits and failure modes; conduct performance and resilience testing, including dependency failure and service recovery exercises. \u2022 Use incident reviews, reliability trends and error-budget consumption to propose improvement priorities and eliminate repetitive manual operational work. \u2022 Maintain runbooks, secure operational access and clean handovers; share knowledge and drive corrective actions through to verified outcomes. \u2022 Within the first six months: Assigned services have documented dependencies, useful health indicators and actionable runbooks; Priority observability and recovery gaps are addressed, with clear incident and customer communication; Initial engineering improvements reduce a measurable source of failure or manual operational effort. \u2022 Within the first twelve months: Agreed reliability measures and recovery performance improve against established baselines; Recurring incidents and unnecessary alerts reduce through verified corrective actions; Reliability findings influence release readiness and engineering priorities, with operational knowledge shared across teams. \u2022 Strong production application support or reliability engineering experience with software products, including complex incidents and customer-facing technical communication. \u2022 Ability to read and debug application code in a relevant language, such as Python, Java, C#, Go or JavaScript/TypeScript, and connect code behaviour with runtime evidence. \u2022 Ability to write maintainable automation or tooling, use Git, review changes and apply appropriate tests before production use. \u2022 Practical experience with observability, distributed tracing, alerting and service health measures; ab

Strong production application support or reliability engineering experience with software products, including complex incidents and customer-facing technical communication. Ability to read and debug application code in a relevant language, such as Python, Java, C#, Go or JavaScript/TypeScript, and connect code behaviour with runtime evidence. Ability to write maintainable automation or tooling, use Git, review changes and apply appropriate tests before production use. Practical experience with observability, distributed tracing, alerting and service health measures.

Improve the production reliability of the platforms, products and applications developed by Inception42 for internal users and external customers. Investigate across code and runtime dependencies, build operational tooling and work with Product Engineering to make services easier to operate and recover. Implement service level indicators and reliability objectives; build and improve logs, metrics, traces, dashboards and alerting; diagnose production issues across code, APIs, queues, databases, containers and underlying services; read source code and trace execution paths to explain failures; write automation and diagnostic tooling; respond to incidents and coordinate technical recovery; communicate with customers and internal users during investigations; improve deployment readiness, health checks and recovery mechanisms; identify capacity limits and conduct performance and resilience testing; use incident reviews and reliability trends to propose improvements; maintain runbooks and handovers; achieve defined milestones within six and twelve months.