Principal Full Stack AI Engineer

Position Summary

Vertex is seeking an AI Full-Stack Engineer to create the next generation of AI-powered applications and agents that deliver practical value across internal and user-facing experiences. This role will own solutions end to end—from user experience and application services to agent orchestration, data access, platform integration, deployment, and production operations. The ideal candidate combines strong full-stack software engineering fundamentals with hands-on experience building AI-enabled products.

This individual will use a forward deployed engineering mindset to work closely with stakeholders, rapidly iterate on real-world use cases, connect applications and agents to enterprise systems, and continuously improve quality through measurement and feedback. The AI Full-Stack Engineer will help shape how secure, reliable, and scalable AI solutions are adopted across Vertex.

• Design, build, and product ionize full-stack AI applications, agents, and multi-step workflows for internal and user-facing use cases
• Apply a forward deployed engineering approach by working closely with end users, product teams, and business stakeholders to solve real workflow problems quickly and effectively
• Build agents that can reason across steps, invoke tools, call APIs, retrieve information, and take actions within defined enterprise guardrails
• Own end-to-end solution delivery across user interfaces, application services, APIs, data access, agent orchestration, and integrations with internal platforms, third-party applications, and business-critical systems
• Develop reusable agent patterns, components, prompts, tools, and orchestration logic that can be scaled across use cases
• Rapidly iterate on agent behavior based on usage data, qualitative feedback, evaluation results, and operational metrics
• Improve agent quality through testing, experimentation, benchmarking, and structured measurement of outcomes
• Partner with platform, integration, data, security, and product teams to ensure agents are secure, reliable, maintainable, and aligned with enterprise architecture
• Help define best practices for agent design, tool use, fallback behavior, escalation paths, and human-in-the-loop workflows
• Support the complete software lifecycle, including architecture, development, integration, deployment, monitoring, troubleshooting, and optimization in production environments
• Contribute to observability practices for agent execution, including logging, tracing, performance tracking, and issue analysis
• Ensure solutions are designed with security, compliance, and responsible AI principles in mind
• Stay current on emerging patterns, frameworks, and technologies in generative AI and agentic systems, and translate them into practical applications for Vertex

• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related technical field; equivalent practical experience may be considered
• Experience in full-stack software engineering, AI engineering, machine learning engineering, or intelligent application development
• Hands-on experience building and operating production applications powered by large language models, AI workflows, or agentic systems
• Experience designing and delivering end-to-end applications across front-end, back-end, APIs, data stores, and enterprise systems
• 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
• Demonstrated ability to move from prototype to production while balancing speed, quality, and operational rigor
• Experience working directly with users or stakeholders to iteratively refine technical solutions based on real-world needs
• Strong problem-solving and systems-thinking skills
• Strong written and verbal communication skills with the ability to work effectively across technical and non-technical teams

• Full-stack application development across modern front-end and back-end technologies
• Large language model application development
• Agentic workflow design and orchestration
• Prompt engineering and prompt iteration
• Tool use and API integration for AI agents
• Multi-step workflow automation
• Rapid prototyping and productionization
• Evaluation, testing, and quality measurement for AI systems
• Application logging, monitoring, and observability
• API design, service development, data modeling, and application architecture
• Distributed systems and service integration
• Secure software development practices
• Enterprise application integration
• Cloud-based application development
• Version control, CI/CD, and deployment practices

• Experience using a forward deployed…