AI Engineer

We are looking for an AI & Data Engineer who is passionate about building production-ready AI and data solutions from the ground up. You'll join a small, high-performing engineering team responsible for developing the AI capabilities and data infrastructure that power our next-generation WealthTech platform.

This isn't about building another chatbot. You'll help create the technology that transforms fragmented financial data into trusted, AI-ready data products used by intelligent applications and autonomous systems.

You'll work closely with the Data, Product, Engineering, and cross-functional teams across the US, Switzerland, Poland, and Singapore.

What You'll do

• Design, build, and maintain AI-powered services and backend applications.
• Develop data pipelines for ingesting, validating, normalizing, enriching, and transforming financial data from multiple sources.
• Build and optimize LLM-based applications, AI agents, and Retrieval-Augmented Generation (RAG) solutions and orchestration workflows.
• Develop APIs and services exposing AI-ready financial data objects.
• Design prompt engineering strategies, model evaluation, benchmarking and observability.
• Evaluate and optimize AI solutions for accuracy, reliability, latency, token usage and cost.
• Collaborate with Product and Engineering teams to translate business requirements into scalable technical solutions.
• Contribute to designing scalable cloud-native architecture and backend services.
• Write clean, maintainable, and well-tested production code.
• Participate in code reviews, architecture discussions, and continuous improvement initiatives.
• Support deployment, monitoring, troubleshooting, and performance optimization of AI applications.
• Continuously evaluate new models, AI technologies, frameworks, and best practices.

What we're looking for?

We are looking for someone who enjoys building software, solving complex engineering problems, and taking ownership.

Requirements

• 3+ years of professional software engineering experience, with strong background in backend, data or machine learning engineering.
• Strong Python programming skills.
• Experience building production-grade backend applications and APIs.
• Hands-on experience building applications with modern LLMs, including AI agents, agentic workflows, RAG architectures and orchestration frameworks (e.g. LangChain, LangGraph, LlamaIndex, Semantic Kernel).
• Experience with prompt engineering, model evaluation and testing AI applications
• Experience working with relational databases (PostgreSQL) and vector databases (e.g. pgvector, Qdrant, Pinecone).
• Understanding of modern data engineering concepts and ETL/data pipelines.
• Experience working with cloud platforms (preferably Azure).
• Familiarity with Docker, Kubernetes, Git, and CI/CD.
• Knowledge of REST APIs and distributed systems.
• Strong problem-solving skills and ability to work independently.
• Very good English communication skills.

• Experience in FinTech, WealthTech, banking, or financial data.
• Experience with MLOps, model monitoring, evaluation, and observability tools (e.g. Langfuse, MLflow).
• Knowledge of Azure AI, Azure OpenAI, Databricks, Microsoft Fabric, or similar technologies.
• Experience with event-driven architectures and messaging systems.
• Understanding of AI governance, security, privacy, and regulated environments.
• Experience working in startups or building products from scratch.

We believe in:

• Mission before ego.
• Builders over managers.
• Small, elite teams.
• Q-SOCS™ - Quality - Speed, Ownership, Challenge, Solutions
• Speed over bureaucracy.
• Ownership and accountability.
• The best idea wins-not the highest title.
• High-quality solutions delivered

You'll help build one of the most ambitious AI and financial data platforms on the market. You'll work on challenging engineering problems, modern AI technologies, and large-scale data infrastructure while collaborating directly with experienced engineers and product leaders. This is an opportunity to build innovative AI solutions from day one and make a real impact on the future of intelligent financial technology.