AI Senior Support Engineer

8 hours, 9 minutes ago
Part-time
Senior
Software Development
Altoros

Altoros

Altoros is a global IT services provider driving digital transformation with cloud-native platforms like Kubernetes and Istio, offering big data expertise and PaaS-based enablement to help organizations gain competitive advantages through modernized in...

IT Services
51-250
Founded 2001

Description

  • Maintain and extend authentication and SSO integration.
  • Own navigation and application shell components in a modern front-end framework such as React or TypeScript.
  • Manage tenant and user administration, including multi-tenancy considerations.
  • 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 Google Cloud Platform data warehouse, primarily BigQuery.
  • Maintain the semantic layer in Cube, including metric definitions and data modeling.
  • Customize and update embedded analytics component files, theming, and SDK integration.
  • Maintain centralized documentation in Confluence, including DBML and database diagrams.
  • Capture ongoing knowledge to support handover, continuity, and backup coverage.
  • Work toward outcome targets such as one-business-day P1 mitigation, defect reduction, and business-hours availability.

Requirements

  • Hands-on AI-first delivery experience using Claude Code or similar AI-assisted engineering tools across the full development lifecycle.
  • Anthropic professional courses and certification are a strong plus, or readiness to complete them.
  • Full-stack development experience with a modern front-end framework such as React or TypeScript.
  • Experience implementing authentication, SSO, and multi-tenant application architecture.
  • Hands-on experience with Dagster or similar orchestration tools.
  • Strong DBT and SQL experience for data transformation.
  • Experience with BigQuery and the Google Cloud Platform data stack.
  • Experience with Cube or a comparable semantic-layer or metrics-layer tool.
  • Familiarity with embedded analytics tooling such as Embeddable, including component customization and theming.
  • Comfort working independently and engaging directly with client stakeholders.
  • Strong documentation discipline using Confluence and DBML or ER diagrams.
  • Availability to work core hours aligned to Chicago time (CT).
  • Background supporting analytics or BI platforms for enterprise or sports/media clients is preferred.
  • Experience setting SLA-style targets and reporting against them is preferred.

Interested in this position?

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