About this role
Vertex seeks a Principal Full Stack AI Engineer to build AI-powered applications and agents for internal and user-facing workflows. The role owns solutions from user experience and application services through agent orchestration, enterprise integration, deployment, and production operations. It uses a forward-deployed approach: work closely with users, product teams, and business stakeholders, iterate on practical use cases, and improve solutions using feedback and measured outcomes.
Responsibilities
- Design, build, and productionize full-stack AI applications, agents, and multi-step workflows. Create agents that reason across steps, retrieve information, invoke tools and APIs, and act within enterprise guardrails.
- Deliver user interfaces, services, APIs, data access, orchestration, and integrations with internal platforms, third-party applications, and business-critical systems. Develop reusable agent components, prompts, tools, and orchestration patterns.
- Evaluate and improve agent behavior through testing, experimentation, benchmarking, usage data, and operational metrics. Establish practices for fallback behavior, escalation, and human-in-the-loop workflows.
- Work with platform, integration, data, security, and product teams on secure, reliable, maintainable solutions. Support architecture, deployment, monitoring, troubleshooting, optimization, logging, tracing, compliance, and responsible AI practices.
Required qualifications
A 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, AI or machine learning engineering, or intelligent application development is required, including production LLM applications, AI workflows, or agentic systems and end-to-end delivery across front-end, back-end, APIs, data stores, and enterprise systems. Candidates must have used AI-assisted development and autonomous coding agents across the software lifecycle and understand AI-native engineering standards, governance, and responsible use. The role also requires stakeholder collaboration, problem-solving, systems thinking, communication, cloud development, secure development, evaluation, observability, version control, and CI/CD. No specific number of years is stated.
Preferred
Forward-deployed delivery; internal copilots or task-oriented agents; orchestration frameworks, agent runtimes, tool-calling and retrieval patterns; enterprise workflow or knowledge-platform integrations; AI evaluation and observability; human-in-the-loop and escalation design; and experience in regulated life-sciences or healthcare settings.
The Boston role offers a choice of hybrid work, with up to two remote days weekly, or five on-site days with ad hoc flexibility, subject to company policy. The stated base-pay range is $166,640–$250,000; the role is eligible for an annual bonus and equity awards. Listed benefits include health coverage, paid time off, educational assistance, student-loan repayment, a commuting subsidy, and a 401(k).