AI/ML Data Engineer

Are you ready to build the future of institutional investing? We are looking for a highly technical AI Data Engineer to join our global Data Science & AI team. This is a unique opportunity to work at the intersection of high-finance and cutting-edge technology, transforming massive alternative datasets—such as clickstream, geolocation, and credit card data—into actionable alpha.

The Offer

• Salary: Up to 40,000 PLN gross (UoP).

• Location: Hybrid (3 days/week from our Warsaw office).

• Impact: Your AI/ML tools will be a direct input to global investment decisions.

• Tech Stack: Build high-capacity systems using Python, dbt, Snowflake, AWS, and the latest LLM frameworks.

• Culture: Work alongside world-class quants and SMEs in a highly creative, exploratory environment built on innovation.

Core Responsibilities

In this role, you won't just be writing code; you'll be building the engine that drives investment discovery.

• AI Tool Development: Design and deploy AI/ML-driven tools to extract unique metadata, create synthetic data, and support the new idea-generation process.

• Data Pipeline Engineering: Build high-capacity, low-latency pipelines to integrate alternative datasets into our data warehouse/lakehouse.

• AI Agent Integration: Make complex data accessible via AI agents to help research teams contextualize and interpret information in real-time.

• Workflow Automation: Apply AI to analysis and production workflows, focusing on enhancing data engineering processes rather than just standard software development.

• Infrastructure & Optimization: Partner with IT to maintain robust tech stacks and continuously refine algorithms to ensure peak performance for our researchers.

• Innovation: Stay at the forefront of LLM technologies (LangChain, LlamaIndex, etc.) to maintain the firm’s competitive edge.

Requirements

Technical Skills:

• 3–5 years of experience in software/data development (tech company background preferred).

• Advanced Data Stack: Strong proficiency in Python (Pandas), SQL, and dbt.

• Cloud & Warehouse: Hands-on experience with Snowflake and AWS (or Azure/GCP).

• AI/LLM Expertise: Familiarity with LLM libraries and APIs (e.g., OpenAI API, LangChain, LlamaIndex).

• Engineering Fundamentals: Solid understanding of data structures, algorithms, and API design.

• Tools: Proficiency in Linux and Docker.

Join Us

If you are passionate about applying AI to complex financial data and want to see your work impact global markets, we want to hear from you. Apply now and help us build the next generation of investment intelligence.