Senior Staff Machine Learning Engineer - Build Agent

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

The Build Agent team is at the forefront of redefining AI-powered Application Development on ServiceNow—powering intelligent, AI-native experiences for developers, admins, and enterprise teams worldwide. Build Agent is ServiceNow's autonomous development agent designed to turn natural language into secure, production-ready enterprise applications.

Build Agent isn't just another AI feature—it represents a fundamental shift in how developers and citizen builders create on the Now Platform. This conversational AI agent automates the complete development lifecycle: analyzing requirements from natural language, generating code and configuration, running automated tests, debugging errors, and deploying applications with built-in governance and security compliance. Build Agent is positioned to democratize application development while maintaining enterprise-grade quality and control. Our goal is to make building applications accessible, lightning-fast, and enjoyable.

What You'll Do in This Role

• Design and develop scalable, maintainable systems that leverage foundation models through effective prompting strategies, orchestration, and tooling.
• Collaborate with product managers to translate requirements into well-architected AI-powered solutions, owning features from prototyping through production deployment.
• Contribute to the design and implementation of new AI-powered products and features while enhancing existing capabilities.
• Build and refine prompt engineering workflows, evaluation frameworks, and retrieval systems to ensure consistent model performance and reliability.
• Design and implement agentic workflows including multi-step task decomposition, tool use, and self-correction loops.
• Integrate automated testing and evaluations into development workflows to measure output quality, latency, and cost across releases.
• Participate in design and code reviews, ensuring best practices in system performance, maintainability, and testability.
• Foster a culture of continuous learning and improvement by sharing best practices in AI engineering, prompt design, and quality evaluation.

Qualifications

• 10+ years of related experience with a bachelor's degree; or 8 years and a master's degree; or a PhD with 5 years' experience; or equivalent work experience
• Proficiency in prompt engineering, including techniques such as chain-of-thought, few-shot prompting, and prompt optimization strategies
• Experience building production systems that integrate foundation models (e.g., Claude, GPT, Gemini) into customer-facing products
• Expertise in writing efficient, well-structured, and maintainable code with strong practices around unit testing, profiling, and performance tuning
• Familiarity with evaluation frameworks and methods for measuring LLM output quality, reliability, and cost-effectiveness
• Knowledge of retrieval-augmented generation (RAG), agent architectures, or other patterns for extending model capabilities
• Experience with code quality systems, static analysis, or CI/CD pipelines

Nice to Have

• Familiarity with agentic patterns such as tool use, planning, and self-correction loops
• Experience with AI-assisted development tools such as Cursor, Windsurf, or similar
• Understanding of security and governance considerations in AI-generated code
• Familiarity with fine-tuning techniques (e.g., supervised fine-tuning, distillation) for understanding model behavior, even if not a primary job function
• Background in AI/ML fundamentals that informs effective use of foundation models

For positions in this location, we offer a base pay of $178,000 - $311,500, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave pr