About the role
We are hiring an SRE focused on observability, automation, and runtime reliability for AI platforms and internal agentic systems. This is not a generic SOC role. It is an engineering role for someone who builds telemetry, automates findings-to-fix loops, improves production readiness, and keeps AI systems measurable, resilient, and controllable in production.
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Location
Riyadh, Saudi Arabia
Responsibilities
- Design and operate the telemetry and observability layer for AI platforms, including audit trails, tool-call logs, correlation IDs, traces, and runtime visibility across service boundaries.
- Build automated findings-to-fix loops for AI and cloud platforms, integrating signals from tooling such as Wiz, Astrix, or future AI security products into pragmatic remediation workflows.
- Implement reliability and hardening controls for internal AI systems, including alerting, health checks, rollback drills, kill-switch validation, rate limiting, and drift detection.
- Codify detections, policies, and operational checks as code where they reduce toil, prevent regressions, and improve platform control.
- Review platform and AI-application changes from a reliability and application-hardening perspective, especially around secrets, telemetry, external calls, risky MCP usage, and production readiness.
- Own AI-platform-specific operational readiness and partner with central IT / EAS / SOC teams for escalations, handoffs, and shared incident workflows when needed.
- Continuously improve production readiness through automation, post-incident learning, and repeatable playbooks for AI runtime issues.
Requirements
- 3+ years in SRE, production engineering, platform operations, or security automation with strong coding ability.
- Hands-on scripting and coding experience, especially Python, with comfort working against APIs, log pipelines, and automation workflows.
- Experience building pragmatic observability and alerting systems in AWS or comparable cloud environments.
- Ability to reduce operational toil through automation while keeping signal quality high and false positives manageable.
- Comfortable with incident handling, rollback thinking, SLA / SLO discussions, and evidence-driven postmortems.
- Interest in AI systems, agent runtimes, and MCP-style integration risks is highly valuable.
Nice to have
- Software engineering background beyond scripting, including code review and testing habits.
- Experience with AI agent runtimes, prompt / tool telemetry, or internal platform hardening for LLM-powered systems.
- Experience with privacy-aware telemetry, compliance-oriented logging, or runtime protection products.
