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.
