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About the Role

Owns the patterns, standards, and technical direction for the Client’s AI-enabled internal engineering platforms — the senior technical authority across core Fin Apps: Forecasting, Finance/Infrastructure data lake, and the Agentic Automation Platform stack.

Responsibilities

Define architecture standards and apply design patterns consistently across core FinOps applications (Forecasting, Infrastructure finance data-lake, Agentic Automation Platform).
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.

Requirements

15+ years in enterprise/platform architecture, including AI-enabled systems.
Demonstrated 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).
Multi-cloud (AWS) architecture experience.
Exposure to financial/FinOps or commitment-tracking systems.
Python/Streamlit familiarity.

Skills

Node.js
GCP
AWS
Snowflake
BigQuery
Python
Streamlit
AI-enabled systems
Agentic platforms
AI-augmented platforms

Location

Austin, TX

Work Type

Onsite
Flexible work from home options available

Experience Level

15+ years

Education Level

GCP Professional Cloud Architect certification (or equivalent depth)