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

Lead the technical delivery of platform reliability and application support for Inception42’s products and applications used by internal colleagues and external customers. You will own complex production investigations, coordinate service recovery, and turn recurring failures into engineering improvements. This is a hands-on technical leadership role spanning application code, runtime dependencies, observability, operational tooling, and customer support, working closely with Product Engineering and infrastructure teams.

Responsibilities:

What You’ll Own

• Set technical standards for production diagnosis, support case quality, observability, runbooks, and recovery across assigned platforms and applications. Mentor engineers and review technical investigations and operational changes.

• Own complex escalated support cases through verified resolution, prioritising customer impact and agreed service commitments. Keep internal users and external customers informed of impact, next steps, workarounds, and progress.

• Lead technical investigation and recovery during major incidents, coordinating Product Engineering, Application Support, Azure Cloud, NetSecOps, Quality Engineering, and Information Security. Maintain clear timelines, handovers, and recovery validation.

• Diagnose failures across application code, APIs, authentication, queues, databases, containers, integrations, and runtime dependencies. Use logs, stack traces, traces, telemetry, and safe database queries to test hypotheses and identify causes.

• Read source code and trace execution paths; create actionable engineering escalations with reproduction steps, environment and version details, correlation identifiers, evidence, and business impact.

• Define and implement service level indicators and agreed reliability objectives with service owners. Improve dashboards and alerting around customer journeys, availability, latency, and successful processing.

• Build maintainable automation, diagnostic tools, and reviewed reliability improvements using version control, appropriate tests, and controlled deployment. Reduce repetitive support work and avoidable escalations.

• Drive release and support readiness with Engineering, including dependency documentation, health checks, operational handover, staged rollout, regression checks, and tested rollback and recovery procedures.

• Assess capacity limits and failure modes; coordinate performance, dependency-failure, and resilience testing with domain engineers and verify recovery outcomes.

• Lead root-cause reviews and track corrective actions to verified completion. Use recurring support demand, incident trends, and error-budget consumption to prioritise reliability and product improvements.

• Protect customer data through approved access, sanitised diagnostics, secure operational tooling, and controlled production data corrections. Maintain accurate runbooks, knowledge articles, and audit evidence.

• Track service commitments, resolution quality, recovery performance, customer experience, and operational effort. Provide clear technical risks and improvement recommendations to service owners and engineering partners.

Qualifications:

What We’re Looking For

• Substantial production application support or reliability engineering experience with software products, including ownership of complex incidents and customer-facing technical investigations.

• Evidence of technical leadership: setting engineering standards, guiding incident recovery, mentoring engineers, and delivering measurable improvements in reliability or support quality.

• Ability to read and debug application source code in a relevant language such as Python, Java, C#, Go, or JavaScript/TypeScript, connecting code behaviour with runtime evidence.

• Ability to build maintainable automation and diagnostic tooling, use Git, review changes, and apply appropriate tests before production use.

• Strong debugging skills across SQL, HTTP, REST APIs, authentication, application integrations, logs, stack traces, and browser diagnostics, with disciplined handling of production data.

• Practical experience with observability, distributed tracing, alerting, and service health measures; working knowledge of Linux, containers, cloud services, databases, and networking across distributed applications.

• Experience with CI/CD, production change validation, incident and problem management, service commitments, and recovery procedures, with sound judgment on access controls and operational risk.

• Clear communication with engineers, customers, and non-technical stakeholders, including calm incident updates, evidence-based escalation, and follow-through across competing priorities.

Nice to Have

• Experience with Azure, Kubernetes or OpenShift, 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 application, data, model-service, queue, and capacity issues.

Participation in agreed production support coverage, on-call or escalation rotas, maintenance, and recovery exercises is required 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.