AI Senior Support Engineer

Location: Remote (Argentina, Uruguay, Colombia)

Company

hirify.global staffs a Senior Support Engineer for a client engagement supporting an analytics platform.

What you will do

• Maintain and extend authentication and SSO integration, and own the platform shell and navigation components.
• Build and maintain data ingestion pipelines, orchestration workflows in Dagster, and transformation logic in dbt and SQL.
• Operate the data stack on Google Cloud Platform (GCP), primarily BigQuery, and maintain the semantic layer in Cube (metrics and data modeling).
• Provide bounded maintenance for embedded analytics components (customization, theming, and keeping the Embeddable SDK current).
• Deliver outcome-based support from month two: P1 issue resolution/mitigation within one business day, defect reduction vs baseline, and business-hours availability once the client is live.
• Maintain centralized documentation in Confluence (including DBML/database diagrams) and ensure clean backup handoff coverage.

Requirements

• AI-first delivery: hands-on with Claude Code (or similar) across the full development lifecycle; Anthropic professional courses/certification is a strong plus.
• Full-stack experience with a modern frontend framework (e.g., React/TypeScript), authentication/SSO, and multi-tenant application architecture.
• Hands-on experience with Dagster for orchestration (or comparable tooling).
• Strong dbt and SQL experience for data transformation.
• Experience with BigQuery and the Google Cloud Platform (GCP) data stack.
• Availability aligned to Chicago time (CT) and ability to work core hours.

Culture & Benefits

• Remote engagement with 80 hours/month and a commercial-model first approach (observe/define in month one, outcome-based delivery from month two).
• AI-augmented delivery using Claude Code inside the client’s own Claude Code/AI-tooling accounts.
• Outcome targets include P1 resolution within one business day, defect reduction against baseline, and business-hours availability once live.
• Spare capacity used for preventative maintenance, hardening, and onboarding new data sources/integrations.
• Backup coverage required to ensure continuity and clean context handoff during absences.