{"id":2391557,"url":"https://alion.io/job/andromeda-customer-reliability-engineer-3","title":"Customer Reliability Engineer","company":{"id":27148,"name":"Andromeda","domain":"andromeda.ai","url":"https://alion.io/company/andromeda","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":91,"open_postings":11,"ghost_share":0,"stale_share":0.545,"repost_share":0,"time_to_fill_p50_days":13,"computed_at":"2026-10-14T06:34:16Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Ansible","optional":false},{"name":"Bash","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Datadog","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"HPC","optional":false},{"name":"InfiniBand","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"NCCL","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"SLURM","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-12T20:34:31Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-14T18:52:52Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Customer Reliability Engineer\nLocation: Remote/EMEA · Full-Time\nAbout Andromeda\nAndromeda is a market and infrastructure platform to buy, sell, and operate compute.\nWe believe demand for compute will grow exponentially. So fast that a handful of vertically integrated providers won't be able to scale across operations, capital, supply chains, and politics to serve it. The result is a massive wave of fragmentation, with AI factories of every shape and size coming to market to fill this demand. Our job is to enable all of that fragmented compute to flow through one platform, delivering reliable capacity to model builders, research labs, and inference providers when they need it. We believe every spare electron should be made productive for AI and we're building the platform that makes that possible.\nWe sit at the center of three forces:\nCompanies that need reliable, high-performance compute fast\n\nA fragmented global supply of GPUs across hyperscalers, neoclouds, and independent data centers\n\nCapital, risk, and operational complexity that most teams are not equipped to manage\n\nWhen we succeed, trillions of dollars of compute will flow through Andromeda. Builders get capacity when they need it. Providers get a reliable way to monetize, operate, and finance infrastructure at scale. Capital gets an easy way to deploy, hedge, and underwrite.\nIn five years, Andromeda won't just participate in the AI infrastructure market. We will shape it.\nThe Role\nOur customers run large AI training and inference workloads on GPU clusters we source from providers worldwide. When a node goes dark or a job dies eight hours into a run, the Customer Reliability Engineer is who they hear from, and who gets it sorted.\nThe job has three parts. You triage incoming issues and debug them at the Linux and Kubernetes layer. You work provider-side to figure out whose fault something actually is and push external providers to fix it. And you build the monitoring and scripts that catch problems before a customer has to tell us.\nYou need to be comfortable in a Linux shell and know how Kubernetes works. You don't need GPU or HPC experience. Most people pick that up here.\nWhat You’ll Do\nTriage and fix customer issues\nOwn issues start to finish: reproduce, diagnose, fix or escalate, close the loop\n\nDebug at the Linux layer: processes, networking, storage, kernel logs, resource contention, systemd, journald\n\nDig into Kubernetes problems like pods stuck pending or crash-looping, node conditions, scheduling failures, resource limits\n\nWork GPU failures: driver and device-plugin issues, XID errors, thermal throttling, nodes that need cordoning or draining, jobs failing across multiple nodes\n\nEscalate when you're past your depth, with the evidence already gathered\n\nHandle incidents\nTake part in a 24/7 on-call rotation\n\nFirst response on alerts and customer-reported outages: assess impact, set severity, pull in the right people\n\nKeep customers updated during incidents. Clear status, honest unknowns, no silence\n\nWrite up what happened, then turn it into a runbook, an alert, or a fix so it costs less next time\n\nPush providers to resolution\nWork out whether a fault is provider-side, ours, or the customer's before it gets handed anywhere\n\nOpen tickets with compute providers and chase them down rather than waiting\n\nTrack recurring provider failures and flag the patterns to the people making sourcing decisions\n\nBuild the tooling\nWrite Python or Bash to automate the checks you'd otherwise run by hand\n\nBuild and improve monitoring: cluster and node health checks, GPU telemetry, dashboards, alerts that fire on real problems\n\nKeep runbooks and customer docs current as you go\n\nWhat We’re Looking For\nReal Linux troubleshooting ability from the command line. You can work a problem through logs, processes, networking, and disk without a script to follow\n\nWorking knowledge of Kubernetes: pods, nodes, deployments, services, scheduling, and how to investigate when one of those breaks\n\nCan write a script in Python or Bash to automate something repetitive\n\nStrong writing. You can explain a technical problem to a frustrated customer clearly and without condescension\n\nGood judgment under pressure. You know what to check first, when to escalate, and how to keep people informed while you're still working it out\n\nWilling to join a 24/7 on-call rotation\n\nStrong Candidates May Have\nHands-on time with NVIDIA GPUs in production: drivers, CUDA, DCGM, the Kubernetes device plugin\n\nExperience with high-performance networking (InfiniBand, RoCE) or NCCL\n\nExperience with HPC or batch schedulers like Slurm\n\nA previous customer-facing technical role: support engineering, TAM, solutions, professional services\n\nKnowledge of Prometheus, Grafana, Datadog, or similar\n\nIAC: Terraform, Ansible, or Helm\n\nGenuine interest in AI infrastructure and how big training jobs behave\n\nWhy You’ll Love It Here\nHigh-growth environment: Get in early at a company at the center of the AI infrastructure boom\n\nCompetitive compensation: + meaningful equity\n\nComprehensive benefits: for you and your dependents, including healthcare, dental, and vision coverage, 401(k), and unlimited PTO\n\nAndromeda Cluster is an equal opportunity employer. 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