Applied AI Engineer
About The Position
We are seeking a highly motivated Applied AI Engineer to contribute to our data science and Ai investment solutions initiatives. This position is open to recent graduates with a strong engineering foundation and a genuine interest in building production-grade AI systems. You will work closely with applied AI researchers, data engineers, and equity analysts to design, build, and maintain the backend infrastructure that powers AI-driven investment research tools. The successful candidate will bring engineering rigor, attention to detail, and a curiosity for how modern AI capabilities can be operationalized into reliable, scalable systems.
Requirements
- Bachelor's or Master's degree in Computer Science or a related technical field
- Strong proficiency in Python with a solid understanding of engineering best practices, including code maintainability, testing, and version control
- Familiarity with backend frameworks (FastAPI or similar) and experience building or consuming RESTful APIs
- Exposure to containerization (Docker) and cloud platforms (AWS preferred); Kubernetes experience is a plus
- Understanding of CI/CD principles and workflow automation tools (e.g., Airflow, cron)
- Exceptional attention to detail and a methodical approach to debugging and system design
Nice To Haves
- Familiarity with LLM APIs or AI agent architectures is a plus, with hands-on exposure through coursework, research, or personal projects preferred
Responsibilities
- Design and manage automated data pipelines and workflow orchestration (e.g., Airflow) to ensure timely, reliable delivery of structured investment data
- Containerize and deploy applications using Docker and Kubernetes, supporting a robust and scalable AI infrastructure on AWS
- Build and maintain RESTful backend APIs using FastAPI to serve AI-powered features and data services to internal research teams
- Integrate and maintain connections to LLM APIs (e.g., OpenAI, Anthropic Claude) and agentic AI frameworks, ensuring reliable and cost-efficient usage
- Implement CI/CD pipelines and apply infrastructure-as-code practices to improve deployment reliability and engineering velocity
- Collaborate cross-functionally with researchers and analysts to translate requirements into well-tested, maintainable backend systems
Benefits
- paid time off
- medical/dental/vision insurance
- retirement
- life insurance
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
