AI Engineer, Private Assets

What you'll do

• Design and implement enterprise-scale AI architectures to process complex, multi-dimensional financial and alternative data.
• Architect end-to-end ML pipelines for multi-modal data sources including structured market data and real-time feeds.
• Develop advanced NLP systems to extract and validate critical metrics from millions of documents and regulatory filings.
• Apply cutting-edge AI techniques like LLMs, computer vision, and deep learning to solve diverse financial use cases.
• Implement MLOps best practices for automated model deployment, monitoring, and continuous improvement across product lines.
• Provide technical guidance and mentorship to engineers on AI/ML best practices and architectural decisions.
• Build conversational AI platforms using generative models, semantic search, and retrieval-augmented generation (RAG) techniques.
• Automate internal engineering tasks by developing and deploying AI agents.

What we're looking for

• Proven expertise in deploying and optimizing large language models and multi-agent architectures.
• Experience architecting Conversational AI platforms using Gen AI, semantic search, and RAG techniques.
• Proficiency with frameworks such as PyTorch, TensorFlow, LangChain, and Langflow.
• Strong knowledge of cloud-native AI infrastructure (Azure, GCP) and distributed inference pipelines.
• Expertise in MLOps best practices, including model deployment, monitoring, and CI/CD pipelines for Gen AI services.
• Solid grounding in data engineering, model evaluation, and system observability.
• Deep knowledge of conversational AI, dialog management, and human-in-the-loop design.
• Demonstrated success in building and mentoring diverse AI and engineering teams.