Altoros

Enterprise IT consulting and cloud-native development

AI Senior Support Engineer

Data EngineeringConfirmed live in the last 24 hours

Part-timeRemote in ArgentinaNo salary listed

About the Job

Requirements

Hands-on experience with Claude Code or similar AI-assisted engineering across the full development lifecycle; Anthropic professional courses and certification are a strong plus, or readiness to complete them.
Full-stack development experience, including a modern front-end framework such as React or TypeScript, authentication and single sign-on 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 data stack.
Experience with Cube or a comparable semantic-layer or metrics-layer tool.
Familiarity with embedded analytics tooling such as Embeddable or similar, component customization, theming, and SDK integration.
Ability to work independently and engage directly with client stakeholders.
Strong documentation discipline, including Confluence and DBML or entity-relationship diagrams.
Availability to work core hours aligned to Chicago time (CT).
Ability to hand off context cleanly to provide backup coverage during absences.

Responsibilities

Maintain and extend authentication and single sign-on integration.
Own navigation and application shell components using a modern front-end framework such as React or TypeScript.
Manage tenant and user management, 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 data warehouse on Google Cloud Platform, primarily BigQuery.
Maintain the semantic layer in Cube, including metric definitions and data modeling.
Customize and update Embeddable component files pulled into the client's repository.
Maintain theming and keep the Embeddable SDK current.
Maintain centralized documentation in Confluence, including DBML/database diagrams.
Capture ongoing knowledge for handover and continuity.
Meet outcome targets from month two: resolve or mitigate P1 issues within one business day, reduce defects against an agreed baseline, and provide business-hours availability once the client is live.
Use spare capacity for preventative maintenance, hardening, and onboarding new data sources or integrations when live issues do not consume the monthly hours.
Support an analytics platform through a month-one observe-and-define phase, including baseline setting and onboarding, followed by outcome-based delivery from month two.

Desired Qualifications

Anthropic professional courses and certification, or readiness to complete them.
Background supporting analytics or business intelligence platforms for enterprise or sports/media clients.
Experience setting service-level-agreement-style targets, such as resolution time and availability, and reporting against them.

AI Senior Support Engineer

Altoros · Argentina (Remote) · Part-time · Posted 2026-07-08

Workplace: remote

Department: Argentina

Description

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

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About the Company

Altoros

Enterprise IT consulting and cloud-native development

Altoros is a global IT consulting and development group that helps large enterprises grow by increasing operational efficiency and delivering products to market faster. It does this through cloud-native development and the application of emerging technologies to create scalable, long-lasting solutions for industries like finance, retail, e-commerce, logistics, healthcare, and wellness. The company works with major technology partners such as Amazon Web Services, Microsoft Azure, VMware, and G-core, and operates delivery centers across multiple time zones to speed up delivery and support global clients. Its differentiators include a 400+ team with two decades of hands-on experience, deep industry domain knowledge, and strategic partnerships that enable enterprise-scale solutions. The goal is to empower organizations to succeed by driving sustainable growth, transforming operations, and bringing innovative products to market more quickly.

Company size: 201-500
Company stage: Not listed
Total funding: Not listed
Headquarters: Pleasanton, CA
Founded: 2001

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