Production Support Engineer, LLM Platform

Qube Rt — Hong Kong Sar · Posted ~5 hours ago

Mid Full-time

Skills

Production support LLM platforms Infrastructure monitoring Troubleshooting Incident triage Model serving Performance monitoring LLM Cloud infrastructure

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Summary ✨ AI‑Generated

Support and operate a production LLM platform used by engineering and business teams. Investigate incidents, monitor infrastructure, troubleshoot model-serving systems and provider integrations, and help maintain predictable latency, throughput, reliability, and capacity as demand increases.

Highlights

Work on a rapidly growing LLM platform with responsibility for availability, stability, performance, and production support. The role combines infrastructure, model-serving, troubleshooting, and cross-functional technical problem solving.

Description

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. Your future role within QRT Provide first- and second-line support for LLM gateway platform, investigating and resolving issues raised by engineering and business users across the firmMonitor and maintain the platform's underlying infrastructure to ensure availability, stability and predictable performance under rapidly growing loadSupport and troubleshoot model-serving backends and provider integrations, model providers, covering latency, throughput, error-rate and capacity issuesTriage incidents affecting model availability — provider instability, connection resets, timeouts, regional slowness — determine whether the cause is platform-side or upstream, and drive to resolution with vendors where requiredSupport the tooling layer built on top of LLM gateway: integrations, developer workspaces (e.g. Coder), coding assistants and API clients, including diagnosing issues introduced by upstream vendor releases running against a gateway-fronted APICoordinate with platform engineering, cloud infrastructure and end-user teams to resolve incidents and minimise disruptionSupport release management and change processes to keep production stable, including staged rollouts, non-prod validation and rollbackBuild tooling and automation to improve monitoring, diagnostics and operational visibility, and to reduce repetitive manual workContribute to the design and implementation of monitoring, dashboards and alerting — for example extending Grafana dashboards covering TTFT, TPOT, percentile latency and failure-rate reportingOwn and improve operational documentation, runbooks and user-facing status communication Your present skillset Experience in a production support, SRE or platform operations role within a fast-paced environment, with strong ownership of issue resolution end to endStrong Linux and Windows system administration skillsProficiency scripting and automating in Python, Bash and/or PowerShellSolid experience with relational databases such as PostgreSQL or SQL Server, including writing queries for investigation and supporting routine operational processesPractical understanding of monitoring and observability: metrics, logs, traces, dashboards and alerting, and the ability to analyse system data to distinguish a platform-wide problem from a localised oneComfortable debugging distributed, API-driven services: HTTP status and error semantics, timeouts, retries, connection resets, rate limiting, caching and latency percentilesFamiliarity with large language model concepts and hosting environments — inference APIs, model gateways/proxies, prompt and context handling, token accounting, streaming responses, prompt cachingExposure to public cloud, ideally AWS (Bedrock, networking, IAM, logging/metrics), and to containerised or Kubernetes-based workloadsAbility to communicate clearly with both engineers and non-technical users, and to manage expectations of senior stakeholders during live incidentsAwareness of data-sensitivity and access-control considerations when routing workloads to third-party model providers Beneficial Experience supporting developer tooling and AI coding assistants (e.g. Claude Code, OpenCode) or IDE/workspace platformsExperience with Grafana, Prometheus or equivalent observability stacks, including building dashboards and alert rulesExperience with CI/CD and infrastructure-as-code (Terraform, Ansible, or similar)Experience operating multi-region services and troubleshooting region-specific performance issues (e.g. APAC latency)Experience acting as the operational interface to third-party vendors and cloud providers during degradations QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.