AI Engineer

We are a world-class investment management firm headquartered in Boston, known for applying advanced technology and data-driven approaches to generate superior returns across global markets. Our culture emphasizes intellectual rigor, innovation, and collaboration. We are building next-generation systems that leverage artificial intelligence to inform investment decisions, streamline operations, and unlock new research capabilities.

We're seeking a highly skilled Software AI Engineer to join our growing AI & Investment Technology team. You'll be responsible for building production-grade AI systems that are deeply integrated with our investment and research platforms. This is a high-impact, hands-on engineering role with exposure to cutting-edge models, rich datasets, and real-world financial challenges.

• Develop and deploy scalable AI solutions for research, portfolio management, and operational efficiency.

• Work closely with data scientists, quants, and investment professionals to translate research models into robust production systems.

• Design and maintain high-performance pipelines for data processing, model training, and real-time inference.

• Contribute to the design of internal AI platforms and tools that support experimentation and deployment at scale.

• Stay current on the latest AI and software engineering developments and assess their potential for adoption.

• Ensure the reliability, security, and observability of AI-driven services running in production environments.

• 4+ years of experience as a software engineer, with a strong focus on AI/ML systems in production.

• Deep proficiency in Python, with experience in frameworks such as PyTorch, TensorFlow, or JAX.

• Strong software engineering fundamentals (data structures, distributed systems, cloud-native architectures).

• Experience deploying and maintaining ML/AI models in real-world settings (batch and real-time inference).

• Familiarity with MLOps practices and tools (Docker, Kubernetes, MLflow, etc.)

• Passion for clean, testable, and maintainable code.

• Bachelor's, Master's, or Ph.D. in Computer Science, Artificial Intelligence, or a related field.

• Exposure to financial markets, trading systems, or quantitative research is a plus-but not required.