As an Applied AI Engineer, you will design, build and iterate AI-driven investment systems end-to-end, translating raw data and ambiguous problem statements into production-grade solutions with measurable investment impact.

You will work across data, models and systems, collaborating closely with portfolio managers, engineers and domain experts to embed AI capabilities directly into core investment workflows.

The ideal candidate combines strong full-stack engineering capabilities with working knowledge of data pipelines and deployment environments, a deep curiosity about the latest advancements in AI technologies and hands-on experience using AI tools to automate, accelerate, and enhance software development.

• Bachelor’s degree of higher in Computer Science, Software Engineering, or related field.

• 3+ years of experience in backend development, with proficiency in a Python-based backend framework (e.g., FastAPI, Django, Flask).

• Familiarity with RDBMS (PostgreSQL), and Vector DB

• Working knowledge of data pipeline development, including data extraction, transformation, and integration processes.

• Experience with cloud and large-scale data platforms (e.g. Databricks, AWS or equivalents) is a plus.

• Working knowledge of modern machine learning workflows (feature engineering, model training, evaluation and iteration) and practical familiarity with LLMs, embeddings and prompt-based systems.

• Demonstrated ability to ship production-grade solutions and leverage AI-native development tools to accelerate coding, testing and documentation.

• Solid understanding of web architecture, APIs, and software design principles.

• Strong analytical, problem-solving, and communication skills, with the ability to collaborate effectively across technical and product teams.

• Deep curiosity and passion for exploring emerging AI technologies and applying them to real-world product development.