AI Engineer

About the role

We are looking for an AI Engineer to join our team. You will work across our full model and agent stack in production, developing and optimizing agentic orchestration workflows, designing and improving our RAG pipeline, and contributing to our custom agent framework. You will also collaborate with data engineers to improve feature store quality, coverage, and serving latency, and build and maintain model monitoring infrastructure.

Responsibilities

• Build, deploy, and maintain production AI models across valuation, forecasting, scoring, and classification tasks - validated against real-world outcomes
• Develop and optimize LangChain-based agentic orchestration workflows and contribute to our custom agent framework
• Design and improve our RAG pipeline and vector search infrastructure for domain-specific retrieval and explainability
• Collaborate with data engineers to improve feature store quality, coverage, and serving latency
• Build and maintain model monitoring infrastructure - drift detection, performance tracking, and automated retraining triggers
• Contribute to the full MLOps lifecycle - experiment tracking, model versioning, deployment pipelines, and rollback protocols

Requirements

We expect you to have strong production ML engineering experience - model training, evaluation, deployment, and live monitoring. You should be comfortable building and maintaining agentic systems using LangChain or equivalent orchestration frameworks, have hands-on experience with LLMs, RAG pipelines, and vector search infrastructure, and be proficient in Python and comfortable working across PyTorch or TensorFlow. Experience with containerised ML systems - Docker, Kubernetes, AWS - is a plus.

Qualifications

Nice to have experience with gradient boosted models (LightGBM, XGBoost) and geospatial ML, familiarity with Snowflake, Pinecone, Apache Kafka, or Spark, background in applied AI in a financial services or data-intensive production setting, and experience with serverless inference - AWS Lambda or equivalent.

Benefits

Work on AI systems that are live in production - agentic orchestration, real-time inference, cross-market model transfer, and retrieval systems operating at scale on proprietary data that doesn't exist anywhere else. Build What's Next: The infrastructure we are building sits at the frontier of applied AI. The models, agents, and reasoning systems you work on here will define how one of the world's largest asset classes operates for decades. Own your work: Small team, no bureaucracy, high trust. Your work ships, your decisions matter, and your fingerprints are on everything we build. Learn from the best: Collaborate with world-class engineers, researchers, and operators who left careers at leading AI labs and financial institutions to build something genuinely new.