2 days ago
Melbourne, AustraliaStaff+
Responsibilities
- Embed with international investment and finance teams to understand workflows, prioritize opportunities, and align engineering capacity with measurable outcomes.
- Architect, build, validate, and deploy AI-enabled applications, automations, agent workflows, and redesigned decision-support processes.
- Replace high- and critical-risk Excel, Access, Tableau, and other EUCT solutions with governed, supportable production capabilities.
- Establish reusable engineering patterns, human-in-the-loop controls, evaluation methods, and implementation guidance for AI-enabled solutions.
- Set technical direction, lead complex delivery, mentor engineers, conduct design and code reviews, and resolve technical or delivery barriers.
- Partner with Product, Engineering, Architecture, Platform, Security, Risk, and business leaders on solution maturity, governance, deployment, reuse, and retirement decisions.
- Communicate delivery status and business value across distributed teams and translate successful engagements into broader organizational capabilities.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field, or an equivalent combination of training and experience.
- At least 7 years of related experience in software engineering, data engineering, data science, or analytics engineering.
- Deep software and data engineering expertise building reliable, maintainable, documented production solutions using modern testing, logging, versioning, and source-control practices.
- Hands-on expertise architecting and deploying AI-enabled and agentic solutions, including prompt engineering, RAG, tool-use patterns, human-in-the-loop controls, and evaluation frameworks.
- Advanced proficiency in Python and the ability to understand and modernize logic in Excel, Access, VBA, SQL, Tableau, and other EUCT solutions.
- Experience with cloud-based AI and data platforms and integrating emerging capabilities into secure, scalable enterprise environments.
- Demonstrated experience leading technical workstreams and delivering production-quality solutions across multiple teams or business areas.
- At least 2 years of experience building and deploying GenAI/LLM-powered solutions in client or production environments is preferred.
- At least 5 years of experience with cloud-based AI and data platforms or products is preferred.
- Deep financial services domain knowledge is highly preferred.
- Ability to work across distributed teams and global time zones while communicating clearly with senior business and technology leaders.
Benefits
- Hybrid working model designed to provide flexibility while supporting in-person learning, collaboration, and connection.
- Opportunity to work across Vanguard’s international business and contribute to responsible AI adoption, investment modernization, and reusable engineering practices.
About Vanguard
Vanguard is an investment management company offering low-cost index and active mutual funds, ETFs, brokerage, retirement plans, and financial advice for individual, institutional, and advisor clients. Founded in 1975 by John C. Bogle and headquartered in Valley Forge, PA, it operates a client-owned structure in which its funds own the firm. Its business model centers on asset-based management and advisory fees.