• Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows

• Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data

• Develop robust APIs and microservices to support model inference, feature serving, and downstream applications

• Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines

• Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements

• Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health

• Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into sc...