AI/ML Engineer

Responsibilities

• Design, prototype, and implement agentic systems for IT automation and resilience using LLMs and agent frameworks (LangChain, LangGraph, etc.).

• Develop multi-agent workflows and coordinate agent collaboration for complex tasks.

• Build and optimize retrieval-augmented generation (RAG) pipelines for knowledge-driven agents.

• Contribute to the development and testing of robust, scalable agentic architectures and infrastructure.

• Collaborate with senior engineers and data scientists in feature development, experiments, and integration of research findings.

• Participate in code reviews, testing, and documentation to ensure quality and reliability.

Required Skills & Experience

• Master’s degree in computer science, Machine Learning, Artificial Intelligence, or a related field.

• 1–3 years of experience (including internships or projects) in AI/ML engineering or software development.

• Solid Python programming skills and familiarity with ML frameworks

• (TensorFlow, PyTorch, scikit-learn).

• Knowledge of LLMs and agentic principles.

• Vanguard Internal Use Only• Experience with vector databases, data pipelines, and retrieval systems.

• Strong problem-solving skills and eagerness to learn new AI techniques and frameworks.

Preferred Qualifications

• Hands-on experience with LangChain, LangGraph or similar agentic frameworks.

• Familiarity with AWS cloud platforms and MLOps tools.

• Contributions to open-source AI/ML projects or agentic frameworks.

• Experience in building autonomous agents, RAG systems, or multi-agent workflows.

Special Factors

Sponsorship

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.