{"id":1675033,"url":"https://alion.io/job/cast-ai-senior-software-engineer-kubernetes-automation-eu","title":"Senior Software Engineer | Kubernetes Automation","company":{"id":54,"name":"CAST AI","domain":"cast.ai","url":"https://alion.io/company/cast-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":84,"open_postings":8,"ghost_share":0,"stale_share":0.625,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-24T06:02:35Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Bulgaria","Croatia","Hungary","Poland","Romania","Estonia","Greece","Latvia","Lithuania","Slovakia"],"countries":["BG","HR","HU","PL","RO","EE","GR","LV","LT","SK"],"hiring_countries":["DE","FR","AT","BE","BG","HR","CY","CZ","DK","FI","HU","IE","IT","NL","PL","RO","ES","SE","EE","GR","LV","LT","LU","MT","PT","SK","SI","GB","NO","CH","IS","LI"],"hiring_countries_total":32,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Karpenter","optional":false},{"name":"Kubernetes","optional":false},{"name":"Amazon EKS","optional":true},{"name":"ArgoCD","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Azure AKS","optional":true},{"name":"C++","optional":true},{"name":"ClickHouse","optional":true},{"name":"containerd","optional":true},{"name":"CRI-O","optional":true},{"name":"eBPF","optional":true},{"name":"GCP","optional":true},{"name":"GitHub","optional":true},{"name":"GitLab","optional":true},{"name":"GitOps","optional":true},{"name":"Google GKE","optional":true},{"name":"Grafana","optional":true},{"name":"gRPC","optional":true},{"name":"Linux","optional":true},{"name":"Loki","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prometheus","optional":true},{"name":"Rest API","optional":true},{"name":"Terraform","optional":true},{"name":"Time Series","optional":true}],"status":"live","first_seen_at":"2026-10-02T07:40:57Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-25T01:39:36Z","board_verified":true,"closed_at":null,"days_open":22,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":22},"description":"What you'll be solving\nA pod is mid-request. The node it's running on is about to disappear - Spot is pulling the instance, or Autoscaler has flagged the node as underutilized and marked it for removal. The safe move is to wait. The profitable move is to act now. Every team in this pipeline is built to close that gap: make the aggressive call and still guarantee nothing breaks.\nThat guarantee is the hard part. Deciding which nodes to kill, which pods to move, and which storage volume to resize is a genuinely hard optimization problem - several of them are P=NP-hard in the general case - and it has to run continuously, in production, faster than a human would ever attempt it by hand. Get it right and clusters run at half the cost. Get it wrong once and you've taken down something live.\nThis posting covers multiple teams working on different pieces of the same automation problem node placement algorithms and provisioning, deep integrations with tools like Karpenter, workload rightsizing (vertical and horizontal), moving running workloads between nodes without interrupting them, storage that scales itself, and GPU capacity optimization across clouds and regions. All of it runs in real time, in production, with no human tuning YAML in the loop.\nThis is a location-specific opportunity. We are currently accepting applications from candidates residing in the following European countries: Bulgaria, Croatia, Estonia, Greece, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Slovenia, and Ukraine.\nRequirements:\nStrong software engineering fundamentals: you design clean abstractions, write maintainable code, and can justify your architecture choices - not just make something work.\n\nProduction experience with Go is strongly preferred; candidates without Go should demonstrate strong systems programming skills in a comparable language.\n\nUnderstanding of Kubernetes internals - autoscaling and networking.\n\nYou've personally driven a complex project end-to-end.\n\nExperience with AI coding agents and agentic development workflows.\n\nYou've used observability tooling in production.\n\nCI/CD and DevOps practices experience.\n\nStrong English skills, both verbal and written.\n\nStartup mindset: adaptable, proactive, and comfortable with ambiguity.\nNice-to-haves:\n\nDeep hands-on experience with cloud platforms (AWS, GCP, or Azure) - including real understanding of how compute, networking, and storage work under the hood.\n\nDeep knowledge of EKS, GKE, or AKS internals.\n\nContainer runtime experience CRI-O, runc, containerd.\n\nCloud storage depth - block storage, CSI, volume management, filesystem internals.\n\nLow-level Linux experience: process internals, packet-level networking (NAT, iptables, conntrack, eBPF, SDN), filesystems, storage.\n\nLow-level systems programming experience in C or C++.\n\nKubernetes or cloud-native OSS contributions.\n\nExperience with AI coding agents and agentic development workflows.\n\nResponsibilities:\nDesign and build distributed systems that operate Kubernetes infrastructure autonomously at scale.\n\nWrite production Go services that interact with AWS, GCP, and Azure APIs for real-time cloud resource management.\n\nOwn features end-to-end: from design through implementation, testing, and production rollout (most projects ship in 1-4 weeks).\n\nDebug complex production issues across cloud providers, Kubernetes clusters, and distributed services.\n\nCollaborate with product and other engineering teams to solve problems that don't have textbook solutions.\n\nWork with time-series data, cloud provider APIs, and Kubernetes control plane internals.\n\nContribute to product direction and backlog - shape what gets built next, not just how it's built.\n\nParticipate in on-call rotation for teams that require it.\n\nTools we use daily:\nProgramming Languages: Go\n\nCloud & Orchestration: Kubernetes, AWS, GCP, Azure\n\nInfrastructure as Code: Terraform\n\nDatabases & Storage: PostgreSQL, Cloud Object Storage, ClickHouse\n\nMessaging & APIs: GCP Pub/Sub, gRPC for internal communication, REST for public APIs\n\nObservability: Prometheus, Grafana, Loki, Tempo\n\nCI/CD & GitOps: GitLab/Github CI with ArgoCD and Kargo\n\nWhat’s in it for you?\nCompetitive salary (€6,500 - €9,000 gross, depending on the level of experience)\nEnjoy a flexible, remote-first global environment.\nCollaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology.\nEquity options.\nGet quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks.\nSpend 10% of your work time on personal projects or self-improvement. \nLearning budget for professional and personal development - including access to international conferences and courses that elevate your skills.\nAnnual hackathon to spark new ideas and strengthen team bonds.\nTeam-building budget and company events to connect with your colleagues.\nEquipment budget to ensure you have everything you need.\nExtra days off to help maintain a healthy work-life balance.\nHiring process\nScreening call with Recruiter\nHiring Manager interview\nTechnical interview (system design)\nLive coding\nCulture Check interview with an executive\n*As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr.\n*Please note that Cast AI does not provide any form of visa sponsorship/work 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