About the role
Vanguard is seeking a talented and motivated AI/ML Engineer to join our team in building agentic systems for IT operations and resilience checking. This role is ideal for early-career professionals who are passionate about AI, autonomous agents, and advanced machine learning techniques. You will work alongside senior data scientists and engineers to develop cutting-edge multi-agent platforms using technologies such as agentic RAG, LangChain, and LangGraph.
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.
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.
About Vanguard Canada
Putting investors first since 1975:
We sell high-quality investment products at the lowest possible price. This is the core of our investment philosophy because we think it’s essential to your investment success.
Unique structure: Vanguard was founded on a simple but revolutionary idea: that an investment company should be run for the sole benefit of its investors. At Vanguard, we don’t have any outside owners, so we don’t need to worry about a stock price or about generating profits for outside owners. This helps us keep costs low, so more of your money stays in your pocket—where it belongs.
A pioneer in the industry: 30 million investors worldwide trust us with over $7 trillion of their savings. Together we’re changing the way the world invests.
About the role
Vanguard is seeking a talented and motivated AI/ML Engineer to join our team in building agentic systems for IT operations and resilience checking. This role is ideal for early-career professionals who are passionate about AI, autonomous agents, and advanced machine learning techniques. You will work alongside senior data scientists and engineers to develop cutting-edge multi-agent platforms using technologies such as agentic RAG, LangChain, and LangGraph.
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.
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.
About Vanguard Canada
Putting investors first since 1975:
We sell high-quality investment products at the lowest possible price. This is the core of our investment philosophy because we think it’s essential to your investment success.
Unique structure: Vanguard was founded on a simple but revolutionary idea: that an investment company should be run for the sole benefit of its investors. At Vanguard, we don’t have any outside owners, so we don’t need to worry about a stock price or about generating profits for outside owners. This helps us keep costs low, so more of your money stays in your pocket—where it belongs.
A pioneer in the industry: 30 million investors worldwide trust us with over $7 trillion of their savings. Together we’re changing the way the world invests.