B
AI Engineer
BOXABL INC
2 hours ago
Full-time
On-site
Las Vegas, Nevada, United States
BOXABL INC
is building an AI-ready Azure data platform that stays accurate, secure, and trusted. In this onsite role in Las Vegas, you will own the pipelines that keep data synced for
Power BI , sales intelligence, and
AI tools and agents , including workflows that read from approved platform sources instead of manual exports.
What you’ll do You will run and improve the platform end to end: ensuring uptime, monitoring, alerting, backups, and incident response. You will also track monthly Azure spend and keep data costs predictable.
Own
Azure Monitor
monitoring and alerting, backups, incident response, and monthly Azure cost.
Build and maintain data feeds from
HubSpot, NetSuite, Tulip, OpenBOM / Oracle PLM, Stripe, Aircall, GA4, and PostHog .
Keep
HubSpot and NetSuite
in sync so customers, orders, and deposits reconcile daily.
Prevent bad writes by fixing data created by AI or voice agents before it pollutes HubSpot.
Model core datasets including the
sales funnel, deposits, sales orders , and
post-sale delivery .
Administer
Power BI
workspaces, datasets, and data sources.
Connect
GrokBot agents, Claude, OpenAI, and Microsoft Copilot
to approved platform data rather than manual exports.
Build retrieval and agent workflows with business teams and keep the
AI Agent Register
current.
Monitor what agents read and write, with emphasis on outreach bots operating in
Microsoft 365
and
HubSpot .
Manage access via
Entra ID (Azure AD)
using SSO, role-based access, and least privilege.
Support
SOC 2
with access reviews, audit logs, change management, and documented runbooks.
Enforce BOXABL's AI acceptable use policy, including preventing company or customer data from being used in unapproved tools.
Core qualifications
4+ years
in data or platform engineering, including
2+ years running production workloads on Azure .
Strong
SQL
and
Python .
Built and maintained
API integrations
with
HubSpot, NetSuite
or comparable CRM/ERP systems.
Shipped at least one production app on
LLM APIs
(OpenAI, Anthropic Claude, or similar).
Experience with
Entra ID , role-based access, and
secrets management
on Azure.
CI/CD with GitHub
and
infrastructure as code .
Calm incident ownership and ability to explain trade-offs to non-technical teams.
First 90 days plan
Day 30:
Map every pipeline, integration, and AI agent that touches company data; ensure alerts cover critical jobs.
Day 60:
Make
HubSpot and NetSuite
reconcile daily; establish one trusted sales-order and deposits dataset in
Power BI , and publish an Azure cost baseline.
Day 90:
Deliver one AI use case in production that reads governed platform data.
How success is measured Data refreshed on schedule ,
HubSpot and NetSuite matching , fewer data incidents, and AI tools using the platform instead of exporting data manually.
Environment and physical demands : Work is performed in an open office environment that supports collaboration inside and outside your department. You must be able to operate standard office equipment (desktop/laptop, printer, scanner). You may walk short distances and occasionally within the factory to perform duties. Most of the day may be spent stationary at a laptop or desktop creating and compiling data and doing extensive reading or research. You may need to exchange ideas verbally and convey detailed spoken instructions accurately.
#J-18808-Ljbffr
is building an AI-ready Azure data platform that stays accurate, secure, and trusted. In this onsite role in Las Vegas, you will own the pipelines that keep data synced for
Power BI , sales intelligence, and
AI tools and agents , including workflows that read from approved platform sources instead of manual exports.
What you’ll do You will run and improve the platform end to end: ensuring uptime, monitoring, alerting, backups, and incident response. You will also track monthly Azure spend and keep data costs predictable.
Own
Azure Monitor
monitoring and alerting, backups, incident response, and monthly Azure cost.
Build and maintain data feeds from
HubSpot, NetSuite, Tulip, OpenBOM / Oracle PLM, Stripe, Aircall, GA4, and PostHog .
Keep
HubSpot and NetSuite
in sync so customers, orders, and deposits reconcile daily.
Prevent bad writes by fixing data created by AI or voice agents before it pollutes HubSpot.
Model core datasets including the
sales funnel, deposits, sales orders , and
post-sale delivery .
Administer
Power BI
workspaces, datasets, and data sources.
Connect
GrokBot agents, Claude, OpenAI, and Microsoft Copilot
to approved platform data rather than manual exports.
Build retrieval and agent workflows with business teams and keep the
AI Agent Register
current.
Monitor what agents read and write, with emphasis on outreach bots operating in
Microsoft 365
and
HubSpot .
Manage access via
Entra ID (Azure AD)
using SSO, role-based access, and least privilege.
Support
SOC 2
with access reviews, audit logs, change management, and documented runbooks.
Enforce BOXABL's AI acceptable use policy, including preventing company or customer data from being used in unapproved tools.
Core qualifications
4+ years
in data or platform engineering, including
2+ years running production workloads on Azure .
Strong
SQL
and
Python .
Built and maintained
API integrations
with
HubSpot, NetSuite
or comparable CRM/ERP systems.
Shipped at least one production app on
LLM APIs
(OpenAI, Anthropic Claude, or similar).
Experience with
Entra ID , role-based access, and
secrets management
on Azure.
CI/CD with GitHub
and
infrastructure as code .
Calm incident ownership and ability to explain trade-offs to non-technical teams.
First 90 days plan
Day 30:
Map every pipeline, integration, and AI agent that touches company data; ensure alerts cover critical jobs.
Day 60:
Make
HubSpot and NetSuite
reconcile daily; establish one trusted sales-order and deposits dataset in
Power BI , and publish an Azure cost baseline.
Day 90:
Deliver one AI use case in production that reads governed platform data.
How success is measured Data refreshed on schedule ,
HubSpot and NetSuite matching , fewer data incidents, and AI tools using the platform instead of exporting data manually.
Environment and physical demands : Work is performed in an open office environment that supports collaboration inside and outside your department. You must be able to operate standard office equipment (desktop/laptop, printer, scanner). You may walk short distances and occasionally within the factory to perform duties. Most of the day may be spent stationary at a laptop or desktop creating and compiling data and doing extensive reading or research. You may need to exchange ideas verbally and convey detailed spoken instructions accurately.
#J-18808-Ljbffr