Senior Principal AI Engineer

Vertex Pharmaceuticals; Boston (MA); On-site; USD 188,000 - 282,000; Full time

Job summary

Vertex Pharmaceuticals in Boston is seeking an engineering leader to 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 onsite role emphasizes standardizing how internal builders create, register, integrate, deploy, and govern their own agents across the enterprise, with a focus on safety, reliability, and scalability.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or related field; advanced degree preferred.
• Significant experience in software engineering or AI platform development.
• Proven track record delivering production-scale AI or ML platforms.
• Experience with distributed systems, APIs, microservices, and cloud-native apps.

Responsibilities

• Lead the build/bring-your-own-agents capability with frameworks, SDKs, and guardrails.
• Deliver shared platform services including model integration and orchestration.
• Define agent lifecycle, quality capabilities, and deployment processes.
• Own developer experience with self-service onboarding and docs.
• Set standards via APIs, contracts, and engineering practices for reliability.

Skills

Distributed systems

APIs

Cloud-native applications

CI/CD

Education

Bachelor's degree in Computer Science

Advanced degree preferred

Tools

CI/CD

Version control

Cloud platforms

Job description

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.

What you’ll do

• 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.

Required qualifications

• 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, CI/CD, version control, code review, and system reliability.
• Deep understanding of AI-native software engineering practices, including standards and governance for responsible use of AI coding assistants and software engineering agents across engineering teams.
• Experience defining architecture, standards, and reusable services for large-scale enterprise environments.
• Experience leading complex technical initiatives and influencing architecture across cross-functional teams.
• Strong communication skills to explain complex technical concepts to varied audiences.
• Ability to balance experimentation speed with production engineering discipline, security, and maintainability.

Technologies you may work with

• APIs, microservices, cloud-native applications, CI/CD, version control
• AI/ML platforms, foundation models, model gateways
• CLIs, vector databases

Compensation and benefits

• Salary range: USD 188,000 - 282,000 per year
• Eligible for an annual bonus and annual equity awards
• Health insurance, dental benefits, and vision benefits
• Generous paid time off, including a week-long company shutdown in Summer and Winter
• Educational assistance programs including student loan repayment
• Generous commuting subsidy
• Matching charitable donations
• 401(k)
• Overtime pay (in accordance with federal and state requirements, for some roles)

Additional information

Vertex is a global biotechnology company that invests in scientific innovation. Vertex is committed to equal employment opportunity and non-discrimination. Vertex is an E-Verify Employer in the United States. Reasonable accommodations are available for qualified individuals with known disabilities in accordance with applicable law.

If you need an accommodation in connection with the hiring process and/or to perform the essential functions of the position, you may request assistance from the recruiter or hiring manager or contact Talent Acquisition at [e-mail].

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