{"id":3453460,"url":"https://alion.io/job/dataart-mle-infrastructure-engineer","title":"MLE Infrastructure Engineer","company":{"id":46984,"name":"DataArt","domain":"dataart.com","url":"https://alion.io/company/dataart-com","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Montevideo, Uruguay"],"countries":["UY"],"hiring_countries":["CO","UY"],"hiring_countries_total":2,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Gitflow","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Grafana","optional":false},{"name":"IAM","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"Prometheus","optional":false},{"name":"Terraform","optional":false},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-10-22T00:00:00Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-31T05:21:07Z","board_verified":true,"closed_at":null,"days_open":9,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":9},"description":"We are looking for a hands on MLE Infrastructure Engineer to strengthen the shared Data and AI platform. You will help define and maintain delivery standards, manage cloud infrastructure and cost, improve security and observability, and support reliable deployments across teams.\nAirline Platform is a shared services initiative that supports Data and AI products with reliable and standardized infrastructure. You will work on infrastructure as code, container orchestration, security automation, and platform reliability in an Agile and DataOps environment.\nDefine and maintain homogeneous CI CD standards and pipelines for data and AI across teams\nManage cloud resources, capacity, and cost through provisioning, autoscaling, and optimization\nOwn identity and access management and centralized credential governance\nAutomate security policies through infrastructure as code and SecOps practices\nRun vulnerability scanning and incident response playbooks\nBuild observability with metrics, dashboards, and proactive alerting for platform and products\nEnsure reliable versioning and deployment standards across the platform\nAct as a platform enabler for product squads on environment and product infrastructure\nProven experience as a Platform, DevOps, or MLOps infrastructure engineer\nExperience with infrastructure as code using Terraform and configuration automation\nExperience with Docker, 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