AI Platform Architect: Lead Multi-Cloud FinOps & AI Platforms

Black Rock Groups

Austin (TX)

On-site

USD 140,000 - 150,000

Full time

14 days+
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Benefits offered by this job

Medical insurance
Vision insurance
Dental insurance
Life insurance
Disability insurance
Paid time off
Parental leave
Sick leave

Job summary

Tech Mahindra in Austin, TX is seeking an AI Platform Architect with 15+ years in enterprise architecture to own patterns, standards, and technical direction for AI-enabled internal platforms, including Forecasting, data lake, and agentic automation stack.

You will define architecture standards across GCP/AWS, lead platform-level decisions, collaborate with Quality Engineering to harden prototypes, and serve as the primary escalation point for engineering leadership.

Qualifications

  • 15+ years in enterprise/platform architecture, including AI-enabled systems.
  • Experience architecting agentic or AI-augmented internal platforms.
  • GCP Professional Cloud Architect certification (or equivalent depth).
  • Working fluency in Node.js and cloud data platforms (Snowflake/BigQuery).

Responsibilities

  • Define architecture standards and apply design patterns consistently across core FinOps applications.
  • Own platform-level technical decisions across the GCP (90%)/AWS cloud split.
  • Set technical direction for MCP development and agentic tooling integration.
  • Partner with Quality Engineering Lead to ensure prototypes are hardened, not rewritten.
  • Act as the primary technical escalation point to the Client engineering leadership.

Skills

Node.js
GCP
BigQuery
Snowflake
AI-enabled systems
Enterprise/platform architecture

Education

GCP Professional Cloud Architect certification

Job description

Tech Mahindra in Austin, TX is seeking an AI Platform Architect with 15+ years in enterprise architecture to own patterns, standards, and technical direction for AI-enabled internal platforms, including Forecasting, data lake, and agentic automation stack.

You will define architecture standards across GCP/AWS, lead platform-level decisions, collaborate with Quality Engineering to harden prototypes, and serve as the primary escalation point for engineering leadership.

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