Lead AI Platform Developer

About the role

This role sits at the center of Treasury's ongoing transformation, focusing on leading the design and evolution of cloud-native data and AI capabilities that directly power Treasury analyst workflows.

Responsibilities

• Cloud & Platform Engineering: Architect, build, and operate cloud-native platforms on GCP
• Own infrastructure patterns for data, analytics, and AI services
• Ensure platforms are secure, scalable, observable, and resilient
• Data Engineering & Analytics: Enable Treasury analysts through LLMs, vector search, and AI tooling
• Design and maintain modern data pipelines and data models
• Enable consistent, trusted data access for Treasury analytics
• AI & Advanced Analytics: Enable AI-driven Treasury workflows using: Vertex AILarge Language Models (LLMs)Vector search / embeddings
• Partner with analysts to productionize AI-assisted research, analysis, and reporting
• Evaluate and integrate emerging open-source AI and data tooling
• DevOps & CI/CD: Establish and enforce CI/CD pipelines for data and AI workloads
• Promote Infrastructure-as-Code and automation-first practices
• Technical Leadership: Act as a technical thought leader within Treasury Technology
• Mentor engineers and analysts on modern data and AI practices
• Influence standards, patterns, and tooling choices across the organization

Requirements

• 8+ years of experience in software, data, or platform engineering
• Strong hands-on experience with cloud-based technologies, preferably GCP
• Advanced proficiency in Python
• Demonstrated experience with open-source data and AI tooling
• Strong background in data engineering and building data systems
• Experience implementing CI/CD, DevOps, and production operations
• Experience with modern analytics and AI stacks, including: dbt, dlt, DuckDBVector search / embeddingsLLM-based systems

Qualifications

• Master's degree in Computer Science, Engineering, or related field
• Experience with large-scale data processing and analytics
• Experience with machine learning and AI frameworks
• Experience with cloud platforms (AWS, Azure, GCP)
• Experience with data warehousing and ETL processes
• Experience with data modeling and database design
• Experience with data visualization tools
• Experience with cloud-native storage and compute
• Experience with data pipeline development and management
• Experience with data quality and governance
• Experience with data security and compliance
• Experience with data privacy and ethical considerations