AI/ML Engineer

AI/ML Engineer

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.
• 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.

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.