AI Platform Developer

About the role

Treasury plays a critical role in safeguarding the company's financial health, managing liquidity, cash flow, funding, and risk across the enterprise. Through an integrated risk-stripe approach spanning market, liquidity, and capital risk, Treasury actively manages the firm's balance sheet to support sustainable business growth. In parallel, Treasury operates deeply embedded cash management and settlement functions that ensure daily obligations are met, while owning fund transfer pricing capabilities that enable the businesses to accurately attribute profitability.

Responsibilities

• Enable AI-driven Treasury workflows using Vertex AI, Large Language Models (LLMs), and vector search/embeddings.
• Build, deploy, and operate AI agents and multi-agent systems at scale for production Treasury workflows.
• Partner with analysts to productionize AI-assisted research, analysis, and reporting.
• Evaluate and integrate emerging open-source AI and data tooling.
• Architect, build, and operate cloud-native platforms on GCP.
• Own infrastructure patterns for data, analytics, AI, and BI services ensuring platforms are secure, scalable, observable, and resilient.
• Design and maintain modern data pipelines and data models.
• Build analytical and BI systems using tools such as dbt, dlt, DuckDB, and cloud-native storage and compute.
• Enable consistent, trusted data access for Treasury analytics and reporting.
• Establish and enforce CI/CD pipelines for data and AI workloads.
• Promote Infrastructure-as-Code and automation-first practices.

Requirements

• 4+ years of experience in software, data, or platform engineering.
• Hands-on experience with Google Cloud Platform (GCP).
• Experience building and scaling AI agents (e.g., agentic frameworks, multi-agent orchestration, tool-use patterns).
• Experience with CI/CD, DevOps, and production operations.
• Proficiency in Python for data engineering, automation, and AI development.

Preferred Qualifications

• Proficiency with Terraform for Infrastructure-as-Code, including collaborative workflows in a team setting.
• Demonstrated experience evaluating, adopting, and contributing to open-source data and AI tooling.
• Background in data engineering and building data systems.
• Exposure to BI and analytics platforms (e.g., Looker, Tableau, or similar) and understanding of how analysts consume data.
• Ability to understand Treasury functions (risk, liquidity, capital, funding) and connect technical work to business outcomes.
• Working knowledge of modern analytics and AI stacks, including: dbt, dlt, DuckDB, vector search/embeddings, LLM-based systems, agentic AI frameworks and orchestration.