Principal Full Stack AI Engineer

Job Description 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.   Key Responsibilities   Design,   build , and productionize   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   Required Qualifications   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   Technical Skills Required   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   Preferred Skills   Experience using a forward deployed engineering or similar embedded delivery model   Experience building internal copilots, assistants, or task-oriented AI agents   Familiarity with orchestration frameworks, agent runtimes, tool-calling architectures, and retrieval patterns   Experience integrating with enterprise collaboration tools, workflow systems, document platforms, or knowledge repositories   Familiarity with evaluation frameworks for AI quality,   groundedness , task completion, and reliability   Experience designing human-in-the-loop workflows and safe failure or escalation mechanisms   Exposure to AI observability, tracing, and operational