Senior Manager AI Reliability Engineering

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About Our Team

Lenovo is building Quantum
, a next‑generation hybrid AI platform that spans Windows, Android, and cloud. As part of this vision, we are expanding the reliability engineering organization powering Qira
, Lenovo's cross‑device Personal AI that operates seamlessly across Lenovo and Motorola products.

We are hiring a Senior Manager, AI Reliability Engineering to lead the engineering teams responsible for Qira's foundational reliability capabilities— including system‑level observability, telemetry, performance engineering, resiliency architecture, and the reliability of Qira's hybrid edge/cloud AI service.

This is a high‑impact leadership role shaping how we measure, operate, and improve reliability across one of Lenovo's most ambitious AI initiatives.

Location
:
Open to remote work in the US. The preferred work location is Chicago, IL.

Additional Locations
:
United States of America – Illinois – Chicago

Engineering Leadership

• Lead and grow multiple engineering teams focused on reliability, observability, and system performance across Qira's hybrid AI ecosystem.
• Define strategy, roadmaps, and priorities to improve reliability, insight, and operational readiness across device, edge, and cloud systems.
• Champion reliability as an engineering discipline through design patterns, best practices, and a culture of continuous improvement.

Observability & Telemetry

• Own the systems that deliver metrics, logs, traces, distributed tracing, AI‑specific signals, dashboards, and alerting.
• Drive the adoption of unified telemetry standards and instrumentation across all Qira components.
• Ensure engineers have actionable insight into performance, reliability, cost, and AI behavior.

Service Reliability & Performance Engineering

• Lead engineering efforts to improve the reliability, performance, and scalability of Qira's service architecture—including inference, retrieval, data pipelines, and hybrid edge/cloud workflows.
• Drive the design and adoption of resilience patterns such as graceful degradation, fallback paths, bulkheads, and rate‑limiting strategies.
• Oversee capacity planning, cost optimization, and performance tuning for high‑throughput AI systems.

System Design & Architectural Influence

• Work with cross‑functional engineering teams to embed reliability early in the design process (“shift left”).
• Guide architectural decisions to ensure Qira's engineering foundations remain stable, observable, and predictable at scale.
• Set service readiness standards for new components entering production.

Cross‑Functional Collaboration

• Partner with Applied AI/ML Engineering, Platform Engineering, Firmware, Product, and Security to align reliability goals with Qira's broader roadmap.
• Collaborate closely with the incident management and operations teams to ensure strong signal quality, runbook depth, and operational tooling.
• Act as a reliability engineering representative in executive and engineering leadership forums.

Team & Talent Development

• Hire and develop world‑class engineers across…