IBU
Cloud Native AI System Engineer
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Role Overview
Senior technical leadership role responsible for designing and engineering AI-native, cloud-native, data-intensive systems supporting network operations across RAN, Core, data, and automation domains. The role combines hands-on systems engineering, architecture, AI-assisted delivery, and technical leadership.
Key Responsibilities
- Own end-to-end system architecture, including APIs, data contracts, resilience, security, and operational controls.
- Translate business and user needs into clear technical specifications, acceptance criteria, and NFRs.
- Lead AI-assisted engineering, using AI agents/tools for design, development, testing, documentation, and automation.
- Design scalable distributed, cloud-native, event-driven, and data-intensive systems.
- Define engineering standards, reusable patterns, AI guardrails, and governance practices.
- Ensure solutions meet security, performance, resilience, quality, and production-readiness standards.
- Work closely with users, architects, product owners, engineers, and test teams to deliver business outcomes.
- Provide technical leadership and coach engineers in systems and AI-native engineering practices.
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Required Skills & Experience
- Strong experience in systems engineering, software architecture, distributed systems, or cloud-native platforms.
- Proven ownership of complex solutions from problem definition through production.
- Hands-on experience with AI-assisted development / coding agents and governing AI-generated outputs.
- Strong knowledge of cloud, APIs, CI/CD, Infrastructure as Code, observability, security, and production support.
- Strong programming skills in Go, Java, C/C++, Rust, or equivalent; Python desirable.
- Strong understanding of algorithms, networking, concurrency, integration patterns, and performance.
- Excellent stakeholder communication and technical decision-making skills.
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Desirable
- AWS architecture experience/certification.
- Telecom / RAN, Core, AIOps, network operations, analytics, or automation experience.
- Experience with event-driven architectures, streaming, lakehouse, data platforms, or AI-agent orchestration.
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