Overview:

Inception42, a G42 company, is the region’s 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 – 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

Overview

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.

Responsibilities:

What You’ll Own

• Understand assigned services end to end, including user journeys, application components, data flows, runtime behaviour and third-party dependencies.

• Implement service level indicators and agreed reliability objectives with service owners, covering user-relevant availability, latency and successful processing.

• Build and improve logs, metrics, traces, dashboards and alerting so operational teams can identify customer impact and locate failures quickly.

• Diagnose production issues across application code, APIs, queues, databases, containers and underlying services, working with domain engineers where needed.

• Read source code and trace execution paths to explain failures; write tested automation, diagnostic tooling and reviewed reliability improvements.

• Respond to incidents, coordinate technical recovery for assigned services and provide clear updates on impact, evidence, mitigation and recovery confidence.

• Work directly with customers and internal users during complex investigations, explaining findings in accessible language and keeping communication aligned with Application Support.

• Improve deployment readiness, health checks and recovery mechanisms with Engineering. Validate changes through staged rollout, operational checks and agreed rollback criteria.

• Identify capacity limits and failure modes; conduct performance and resilience testing, including dependency failure and service recovery exercises.

• Use incident reviews, reliability trends and error-budget consumption to propose improvement priorities and eliminate repetitive manual operational work.

• Maintain runbooks, secure operational access and clean handovers; share knowledge and drive corrective actions through to verified outcomes.

• 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.

• 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.

Qualifications:

What We’re Looking For

• 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; able to distinguish symptoms from contributing causes.

• Working knowledge of Linux, containers, cloud services, APIs, databases and networking sufficient to troubleshoot across a distributed application.

• Experience with CI/CD, production change validation, incident response and recovery, with clear attention to access controls and customer data.

• Strong communication and independent problem-solving skills, with evidence of reducing recurring failures or operational effort through engineering.

Nice to Have

• Experience with Kubernetes or OpenShift, Azure, infrastructure as code and open observability tooling.

• Experience implementing service level objectives, error-budget practices, load testing or resilience exercises.

• Exposure to AI inference or data-processing platforms, including dependencies, queue behaviour and specialised capacity constraints.

Participates in an agreed production on-call rota, incident response, maintenance and recovery exercises according to service commitments.

Inception42 is building AI systems designed for practical deployment at scale — across industries, infrastructure, and national-level initiatives.

If you want to work close to both advanced AI capability and real-world execution, we’d like to hear from you.