Senior AI/ML Engineer

Vanguard; Town of Charlotte (NY); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Vanguard is hiring for an AI/ML engineer to design and implement multi-agent systems and retrieval-augmented pipelines. You will collaborate with senior engineers and data scientists on feature development, experiments, and integration of research findings.

The role requires a Master’s degree in a related field and 5–8 years of experience, with strong Python skills and experience with TensorFlow/PyTorch. Hybrid work model and collaboration across teams are emphasized.

Qualifications

• Master’s degree in computer science, ML, AI, or related field.
• 5–8 years of AI/ML engineering or software development experience.
• Proficient Python programming with ML frameworks.
• Strong knowledge of LLMs and agentic principles.
• Experience with vector databases, data pipelines, and retrieval systems.
• Strong problem-solving and quick learning of new AI techniques.

Responsibilities

• Design, prototype, and implement agentic systems for IT automation and resilience using LLMs and agent frameworks.
• Develop multi-agent workflows and coordinate agent collaboration for complex tasks.
• Build and optimize retrieval-augmented generation pipelines for knowledge-driven agents.
• Contribute to 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.

Skills

Python

ML Engineering

LLMs

Vector Databases

Data Pipelines

Education

Master’s degree in Computer Science

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Responsibilities

• Design, prototype, and implement agentic systems for IT automation and resilience using LLMs and agent frameworks

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

• Build and optimize retrieval-augmented generation 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.

• 5-8 years of experience 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 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

Vanguard is not offering visa sponsorship for this position.

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.