AI Senior Support Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 16h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 95d ago
The date the source published, not the day we noticed it (2026-07-08). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Argentina, Uruguay, Colombia
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $5,500–7,250/mo
Middle 50% of 13 listings that do state pay — Engineering · Senior · Argentina · USD/month. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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Workable employer's own board first seen 17h ago · last seen just now
The listing
AI Senior Support Engineer
Hours: Aligned to Chicago time (CT) · Engagement: 80 hrs/month, full-stack + data stack remit
About the Role
Altoros 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).
AI-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.
Scope & Responsibilities
Platform Shell
- Maintain and extend authentication and SSO integration
- Own navigation and application shell components (modern front-end framework, e.g., React / TypeScript)
- Manage tenant and user management, including multi-tenancy considerations
Data & Semantic Stack
- Build and maintain data ingestion pipelines
- Operate and extend orchestration workflows in Dagster
- Develop and maintain transformation logic in dbt and SQL
- Work with the data warehouse on Google Cloud Platform (GCP), primarily BigQuery
- Maintain the semantic layer in Cube, including metric definitions and data modeling
Embedded Analytics (light, bounded)
- Customize and update Embeddable component files pulled into the client's repo
- Maintain theming and keep the Embeddable SDK current
- Note: Embeddable itself handles the builder, embed serving/rendering, security tokens, and multi-tenancy: this is a maintenance layer, not a build-from-scratch effort
Delivery & Documentation
- Maintain centralized documentation in Confluence, including DBML/database diagrams
- Capture ongoing knowledge for handover and continuity purposes
- Work 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
- Use spare capacity (when live issues don't consume the monthly band) on preventative maintenance, hardening, and onboarding new data sources/integrations
Required Skills & Experience
- AI-first delivery (core requirement): hands-on with Claude Code (or similar) / AI-assisted engineering across the full development lifecycle; Anthropic's professional courses and certification are a strong plus (or readiness to complete them)
- Full-stack development experience, including a modern front-end framework (e.g. React / TypeScript), authentication/SSO implementation, and multi-tenant application architecture
- Hands-on experience with Dagster for orchestration (or similar tools)
- Strong DBT and SQL experience for data transformation
- Experience with BigQuery and the Google Cloud Platform (GCP) data stack
- Experience with Cube or a comparable semantic-layer / metrics-layer tool
- Familiarity with embedded analytics tooling (Embeddable or similar), component customization, theming, SDK integration
- Comfortable working independently and engaging directly with client stakeholders
- Strong documentation discipline: Confluence, DBML/ER diagrams
- Available to work core hours aligned to Chicago time (CT)
Nice to Have
- Background supporting analytics/BI platforms for enterprise or sports/media clients
- Experience setting SLA style targets (resolution time, availability) and reporting against them
Engagement Details
- 80 hours/month, full remit across platform shell, data/semantic stack, and Embeddable upkeep
- Backup coverage required for continuity during absences: candidate should be able to hand off context cleanly