Software Development Manager

About the Team
NetSuite’s AI Platform organization is building the next generation of intelligent, agentic, and context-aware capabilities that will power NetSuite Next. The AI Evaluation Platform is a critical foundational component ensuring all AI experiences—LLM-powered workflows, agents, recommendations, and model-driven insights—are safe, reliable, high quality, and compliant.

We build the systems used across engineering teams to evaluate LLMs, test agent behaviors, measure quality, and enforce governance for all AI features across the NetSuite product suite.

Role Overview:

We are seeking a Software Development Manager to lead the engineering team responsible for the AI Evaluation Platform. In this role, you will own the strategy, execution, and people leadership for the platform that powers AI quality measurement, regression testing, agentic evaluation, fleet validation, and model governance across NetSuite.

This is a highly visible, cross-functional role that partners closely with AI Platform, Product, Data Science, ADP (Agent Development Platform), MLP, Security, and Value Stream engineering teams.

You will be responsible for managing a team that designs, develops, troubleshoots and debugs software programs for AI evaluation, governance, and feedback collection.

As a manager of the software engineering division, you will apply your knowledge of software architecture to manage software development tasks associated with developing, debugging or designing software applications, operating systems and databases according to provided design specifications. Build enhancements within an existing software architecture and occasionally suggest improvements to the architecture.

Leadership & Strategy

• Own the end-to-end roadmap, execution, and delivery of the AI Evaluation Platform.
• Lead a team of 5–8 software engineers, with responsibility for hiring, mentoring, career development, and performance management.
• Establish engineering best practices, operational excellence standards, and quality gates for all AI evaluation workflows.
• Partner with Product, Security, and Governance stakeholders to define evaluation metrics, safety requirements, and compliance guidelines.

Technical Ownership

• Drive development of automated agentic evaluation frameworks, LLM quality benchmarks, and safety testing pipelines.
• Oversee fleet validation infrastructure ensuring reliability, correctness, and scale across thousands of customer accounts.
• Ensure the platform supports multiple model families (GPT-5, GPT-4.x, GPT-OSS, custom domain models, etc.).
• Integrate evaluation pipelines with ADP, MLP, Data Platform, and Feedback
• Set architectural direction and long-term scalability strategy for evaluation systems.

Cross Functional Collaboration

• Work closely with AI/ML teams to validate model performance, assess regression risks, and guide model selection.
• Partner with Value Stream teams to ensure new AI features meet quality, accuracy, and safety standards before release.
• Collaborate with ProdSec/AppSec to implement governance enforcement and responsible AI frameworks.
• Interface with senior engineering and executive leadership on progress, risks, and strategic impact.