{"id":848729,"url":"https://alion.io/job/altoros-ai-senior-support-engineer","title":"AI Senior Support Engineer","company":{"id":63691,"name":"Altoros","domain":"altoros.com","url":"https://alion.io/company/altoros","size_band":"1-10","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":3,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-20T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"part_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["AR","CO","UY"],"hiring_countries_total":3,"salary":null,"salary_estimate":{"min_usd":51000,"max_usd":131000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2216},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anthropic","optional":false},{"name":"BigQuery","optional":false},{"name":"Claude Code","optional":false},{"name":"Confluence","optional":false},{"name":"Dagster","optional":false},{"name":"dbt","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"SLI/SLO/SLA","optional":true}],"status":"live","first_seen_at":"2026-07-08T00:00:00Z","employer_posted_date":"2026-07-08","last_verified_at":"2026-10-20T04:24:55Z","board_verified":true,"closed_at":null,"days_open":104,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":104},"description":"AI Senior Support Engineer\nHours: Aligned to Chicago time (CT) · Engagement: 80 hrs/month, full-stack + data stack remit\nAbout the Role\nAltoros is staffing a Senior Support Engineer for a client engagement supporting an analytics platform. This is a full-stack and data-stack role: the engineer owns the platform shell, the ingestion and semantic layer, and a bounded amount of embedded analytics component upkeep. The role is commercial-model first: month one is an observe and define phase (baseline setting, onboarding), with the engagement shifting toward outcome-based delivery from month two (issue resolution time, defect reduction against baseline, availability targets).\nAI-augmented delivery is central to this role and one of its most important elements. Working AI-first with Claude Code is how a single engineer credibly covers this full remit. Altoros builds its delivery on Anthropic's professional courses and certification, and the engineer uses Claude Code across the full range of work - maintenance, bug-fixing, and data work, not just new development - operating inside the client's own Claude Code / AI-tooling accounts.\nScope & Responsibilities\nPlatform Shell\nMaintain and extend authentication and SSO integration\nOwn navigation and application shell components (modern front-end framework, e.g., React / TypeScript)\nManage tenant and user management, including multi-tenancy considerations\nData & Semantic Stack\nBuild and maintain data ingestion pipelines\nOperate and extend orchestration workflows in Dagster\nDevelop and maintain transformation logic in dbt and SQL\nWork with the data warehouse on Google Cloud Platform (GCP), primarily BigQuery\nMaintain the semantic layer in Cube, including metric definitions and data modeling\nEmbedded Analytics (light, bounded)\nCustomize and update Embeddable component files pulled into the client's repo\nMaintain theming and keep the Embeddable SDK current\nNote: Embeddable itself handles the builder, embed serving/rendering, security tokens, and multi-tenancy: this is a maintenance layer, not a build-from-scratch effort\nDelivery & Documentation\nMaintain centralized documentation in Confluence, including DBML/database diagrams\nCapture ongoing knowledge for handover and continuity purposes\nWork to defined outcome targets from month two: P1 issue resolution/mitigation within one business day, defect reduction against an agreed baseline, and business-hours availability once the client is live\nUse spare capacity (when live issues don't consume the monthly band) on preventative maintenance, hardening, and onboarding new data sources/integrations\nRequired Skills & Experience\nAI-first delivery (core requirement): hands-on with Claude Code (or similar) / AI-assisted engineering across the full development lifecycle; 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