AI Engineer NYC Livestream | Bridgewater, Two Sigma, Arize, Coatue, Nous (Hermes), Gen. Intuition

AI engineering in regulated sectors like finance requires balancing agent autonomy with rigorous safety and compliance. Organizations are shifting from simple chatbot implementations to "always-on" agentic systems that manage complex, long-horizon workflows. Key strategies include building specialized data platforms like Bridgewater’s "Vault" to align unstructured data with internal ontologies, and implementing multi-layered guardrails—such as agent registries and runtime authorization—to prevent catastrophic operational errors. As AI takes on more development tasks, the industry is redefining code quality, distinguishing between "durable" software requiring high rigor and "disposable" software enabled by AI. Ultimately, the transition to AI-native operations hinges on observability, where agents act as primary consumers of telemetry data, and the implementation of intent-based authorization to ensure agents operate within defined missions while maintaining human accountability.