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NetSuite · 1 month ago

Senior Research Engineer - Agentic AI

United States

Full-time

Remote

Mid, Senior Level

3+ years exp

NetSuite is part of Oracle Analytics, where they are building the next generation of enterprise AI products for intelligent data analysis at scale. The Senior Research Engineer will lead innovation in agentic systems and human-in-the-loop experiences, focusing on research, architecture, and prototyping of advanced AI agents and interactive UIs.

Cloud ComputingComputerCRMiOSSaaSSoftware

Responsibilities

Research, architect, and prototype next‑generation agents (tool use, planning, orchestration) and efficiency techniques (distillation, quantization, retrieval, caching) that improve latency, cost, and quality for enterprise workloads

Design and build rich, interactive UIs to enable human oversight, feedback, and troubleshooting—closing the loop between model behavior, evaluation, and product impact

Partnering closely with applied scientists, research engineers, and product teams

Take your solutions from lab to production, driving measurable outcomes and shipping globally scaled intelligent applications

Design novel solutions that turn business requirements into intuitive experiences for review, feedback, and oversight—spanning prompt/tool orchestration consoles, evaluation dashboards, trace/telemetry views, safety and guardrail configuration, and annotation/feedback loops

Demonstrated experience taking science prototypes to production is essential, including integrating LLM backends (streaming, caching, retrieval, tool use), instrumenting rigorous evaluation (offline metrics, A/B testing, rubrics), and ensuring reliability, performance, accessibility, and security

Hands-on proficiency with modern web stacks (e.g., TypeScript, React, design systems, data visualization), real-time collaboration, and observability is a must

Familiarity with LLM post-training/fine-tuning, alignment, and agent orchestration is strongly preferred to partner effectively with modeling teams

Experience visualizing and interacting with structured, tabular, graph, or time-series data is a strong plus

Thrive in fast-paced environments, reduce ambiguity through prototyping and user testing, and own outcomes end to end—from concept to globally scaled deployment