Senior Principal AI Engineer

Vertex Pharmaceuticals is building enterprise capabilities that help teams integrate and operationalize agentic AI in production. In this role, you will design, build, and optimize shared platform services that support build/bring-your-own-agents workflows, from model integration and orchestration to evaluation, observability, and agent lifecycle management.

This position is based in Boston, MA (onsite) and focuses on standardizing how internal builders create, register, integrate, deploy, and govern their own agents across the enterprise.

• Lead the build/bring-your-own-agents capability (primary focus) by creating the frameworks, SDKs, templates, interfaces, and guardrails that enable teams to operationalize custom agents on shared platform standards.
• Deliver shared platform services including model integration, prompt and workflow orchestration, tool use, memory patterns, and agentic task coordination that other teams build against.
• Define agent lifecycle and quality capabilities such as registration, configuration, testing, deployment, versioning, monitoring, retirement, and the evaluation and benchmarking frameworks that support them.
• Own and improve the developer experience with self-service onboarding, documentation, reference implementations, enablement resources, and tooling that accelerates the path from idea to production.
• Set standards and provide technical leadership through platform APIs, service contracts, architecture patterns, and engineering practices that keep custom agents safe, reliable, and supportable.
• Architect and implement shared AI/agentic platform services to support enterprise AI products and internal workflows, including hardened, maintainable, production-grade implementations.
• Establish evaluation and validation frameworks for AI model, agent, and workflow performance using reusable frameworks and services.
• Build observability across AI workloads with capabilities for monitoring, tracing, logging, and alerting across agent interactions.
• Optimize production performance for scalability, latency, reliability, and cost efficiency for AI and agentic systems.
• Integrate with enterprise infrastructure by building and maintaining robust integrations with foundation models, model gateways, APIs, enterprise tools, and related AI infrastructure.
• Partner across teams including product, data, engineering, security, and architecture to enable enterprise-ready AI solutions.
• Support governance and responsible AI through measurable controls, policy enforcement, and technical safeguards for agent behavior.
• Drive adoption by creating reusable components, documentation, onboarding patterns, and developer enablement resources.
• Mentor engineers and provide technical leadership across AI platform initiatives.
• Evaluate emerging tools and patterns in generative AI and agentic systems to inform platform strategy.

• Bachelor’s degree in Computer Science
  , Software Engineering
  , Machine Learning
  , Data Engineering
  , or a related technical field;
  advanced degree preferred
  .
• Significant industry experience in software engineering, machine learning engineering, or AI platform development, including experience in senior or principal-level technical roles.
• Proven track record designing and delivering production-scale AI or ML platforms
  .
• Strong experience building distributed systems
  , APIs, microservices, and cloud-native applications.
• Demonstrated experience operationalizing machine learning, generative AI, or agent-based solutions in enterprise environments.
• Experience designing extensible platform capabilities that enable internal teams to build or integrate custom applications, tools, or services.
• Deep understanding of software engineering best practices including testing,…