Software Engineer, Data & Applied AI

Software Engineer, Data & Applied AI Overview

• The Software Engineer, Data & Applied AI will contribute to building and maintaining software and data infrastructure supporting AI applications in investment research and operations.
• Collaborate closely with investors and technical leads to design, develop, and deploy impactful technical solutions for sophisticated workflows.
• Focus on backend systems, data pipelines, internal applications, and applied AI workflows to enhance decision-making processes.
• Work in a highly collaborative environment, engaging directly with users to refine and improve systems for daily use.
• Receive mentorship and architectural guidance while taking ownership of projects from inception to production deployment.
• Contribute to the development of scalable technical solutions, including applications, templates, and reusable workflows.
• Enable users to effectively incorporate AI tools into their workflows, ensuring accuracy and operational standards.
• Join a dynamic team committed to innovation and excellence in software engineering and AI enablement.

• Develop and maintain Python backend services, APIs, databases, and integrations for investment and operational workflows.
• Design and implement ETL pipelines for structured and unstructured data, ensuring data quality and reliability.
• Integrate external data vendors and internal systems to streamline data ingestion and processing.
• Build lightweight internal applications for investment and operational users to enhance productivity.
• Develop applied AI workflows, including LLM APIs, agents, and evaluation systems for advanced capabilities.
• Ensure workflows are secure, reliable, and maintainable, adhering to best practices in software engineering.
• Collaborate with users to translate open-ended problems into technical solutions and refine systems post-deployment.
• Document systems and provide ongoing support to ensure operational success and user satisfaction.

• Bachelor of Science (BS) degree in Computer Science, Engineering, or a related field.
• 2-4 years of experience in software engineering, with demonstrated ability in backend development and data-intensive applications.
• Proficiency in Python programming and SQL fundamentals, with experience in relational databases and data modeling.
• Experience with modern development tools, including Git, testing frameworks, and CI/CD pipelines.
• Familiarity with Databricks, Azure, Docker, and FastAPI is advantageous but not mandatory.
• Knowledge of applied AI workflows, including LLM APIs and agentic systems, is highly desirable.
• Strong problem-solving skills and ability to work collaboratively with technical and non-technical stakeholders.
• Commitment to continuous learning and professional growth in software engineering and AI enablement.