Principal Full Stack AI Engineer

Responsibilities

• Design, build, and productionize full-stack AI applications, agents, and multi-step workflows for internal and user-facing use cases
• Use a forward deployed engineering approach by partnering with end users, product teams, and business stakeholders to solve 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 delivery across user interfaces, application services, APIs, data access, agent orchestration, and integrations with internal platforms, third-party applications, and business-critical systems
• Create reusable agent patterns, components, prompts, tools, and orchestration logic that can be scaled across use cases
• 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 support secure, reliable, maintainable agent solutions 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 full software lifecycle including architecture, development, integration, deployment, monitoring, troubleshooting, and optimization in production environments
• Contribute to observability for agent execution, including logging, tracing, performance tracking, and issue analysis
• Design solutions with security, compliance, and responsible AI principles in mind
• Stay current on emerging patterns, frameworks, and technologies in generative AI and agentic systems, translating them into practical applications for Vertex

Requirements

• 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 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, including establishing standards, governance, and best practices for responsible use of AI coding assistants and software engineering agents across engineering teams
• Proven 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 collaborate effectively across technical and non-technical teams

Benefits

• Eligible for an annual bonus
• Annual equity awards
• Some roles may also be eligible for overtime pay, in accordance with federal and state requirements
• Medical, dental and vision benefits
• Generous paid time off (including a week-long company shutdown in the Summer and the Winter)
• Educational assistance programs including student loan repayment
• Generous commuting subsidy
• Matching charitable donations
• 401(k)

Technical Skills

• 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 analytics
• Experience in regulated industries such as biotechnology, pharmaceuticals, healthcare, or life sciences

Compensation and Flex Designation

Pay range: $166,640 - $250,000 per year.

Flex designation: Hybrid-Eligible or On-Site Eligible.

Flex eligibility status: For this hybrid-eligible role, you can choose to be designated as:

• Hybrid: work remotely up to two days per week; or select
• On-Site: work five days per week on-site with ad hoc flexibility

Note: The Flex status for this position is subject to Vertex’s Policy on Flex @ Vertex Program and may be changed at any time.