Senior Principal AI Engineer
Boston, MA Hybrid
$188,000–$282,000 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
Vertex is seeking a Senior Principal AI Engineer to define and build the foundational enterprise AI platform that powers intelligent applications across the enterprise. This role will lead the design and implementation of scalable, secure, and reusable capabilities for agentic AI, with a strong focus on retrieval-augmented generation (RAG), orchestration frameworks, evaluation systems, and platform architecture. In addition to building out the core platform, this engineer will own the vision and day-to-day operations of a centralized AI Gateway / Control Plane / Control Tower that enables agent monitoring, observability, policy enforcement, governance, and operational controls across AI solutions at Vertex. This is a highly strategic and hands-on role for an experienced AI engineer who is excited to shape enterprise AI architecture, standards, and long-term technical direction. The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards. Some roles may also be eligible for overtime pay, in accordance with federal and state requirements. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.
What you'll bring
- Retrieval-Augmented Generation (RAG)
- Knowledge retrieval systems
- Advanced degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related technical field; or equivalent combination of education and experience
- 10 + years of experience designing and building enterprise-grade AI/ML platforms and distributed systems
- Deep expertise in agentic AI architectures, LLM-based applications, and platform engineering
- Proven experience with retrieval-augmented generation (RAG) systems, vector search, document retrieval, and knowledge integration patterns
- Strong experience with AI orchestration frameworks, workflow engines, and multi-step agent execution patterns
- Demonstrated experience designing centralized operational platforms for monitoring, governance, observability, and control
- Demonstrated experience using AI-assisted software development and autonomous coding agents to design, generate, test, review, debug, optimize, and refactor code across complex enterprise systems.
- Deep understanding of AI-native software engineering practices and experience establishing standards, governance, and best practices for the responsible use of AI coding assistants and software engineering agents across engineering teams
- Experience defining architecture, standards, and reusable services for large-scale enterprise environments
- Strong understanding of AI system evaluation, quality measurement, and performance optimization