Senior Principal AI Engineer

Job Description

Vertex is seeking a   Senior   Principal AI Engineer to define and build the foundational enterprise AI platform that powers intelligent applications across the enterprise. This role will lead the design and implementation of scalable, secure, and reusable capabilities for agentic AI, with a strong focus on retrieval-augmented generation (RAG), orchestration frameworks, evaluation systems, and platform architecture.

In addition to building out the core platform, this   engineer   will own the vision   and day-to-day operations of   a centralized AI   Gateway   / Control Plane /   Control Tower   that enables agent monitoring, observability, policy enforcement, governance, and operational controls across AI solutions at Vertex. This is a highly strategic and hands-on role for an experienced AI   engineer   who is excited to shape enterprise AI architecture, standards, and long-term technical direction.

Key Responsibilities

Agentic AI platform :   the shared architecture, services, and reusable capabilities that make it faster and safer to build AI-powered applications across Vertex

AI Control Tower operations: standing up and running the centralized control plane for agent monitoring, observability, telemetry, policy enforcement, guardrails, usage analytics, and auditability

Own the strategy, architecture, implementation, and day-to-day operation of the centralized AI Gateway / Control Tower as the enterprise control point for model access, routing, governance, cost management, and operational oversight

Intelligent model routing, provider abstraction, fallback, failover, rate limiting, and workload optimization across approved models

AI FinOps, including token and consumption visibility, budgeting, chargeback/ showback , cost allocation, forecasting, and model-cost optimization

Centralized guardrails for content safety, prompt-injection defense, data-loss prevention, sensitive-data handling, and responsible AI policy enforcement

Identity, access, security, privacy, regulatory compliance, and lifecycle governance controls for models, agents, tools, and AI interactions

End-to-end observability, telemetry, quality monitoring, latency and reliability metrics, incident response, and operational health management

Usage analytics, immutable audit trails, policy evidence, risk reporting, and executive-level transparency across the enterprise AI estate

Model onboarding, approval, versioning, deprecation, resiliency, capacity management, and third-party provider governance

Retrieval and knowledge systems: RAG pipelines, vector search, document retrieval, and the grounding patterns that make enterprise content usable by agents

Agent lifecycle and quality: deployment, versioning, evaluation frameworks, reliability measurement, and continuous improvement of agents in production

Standards and technical leadership: platform APIs, service contracts, architecture patterns, and the engineering practices other teams build against

Define the technical vision, architecture, and roadmap for Vertex’s enterprise agentic AI platform

Design and build reusable platform services that accelerate development of safe, reliable, and scalable AI-powered applications

Lead architecture and implementation for RAG pipelines, knowledge retrieval systems, prompt workflows, tool use, and agent orchestration

Establish core frameworks for agent lifecycle management, including deployment, monitoring, observability, evaluation, and continuous improvement

Develop scalable infrastructure patterns for enterprise AI workloads, including model integration, data access, and orchestration services

Partner closely with product, engineering, data, security, and UX teams to deliver common AI platform capabilities that support multiple use cases across Vertex

Establish best practices for AI reliability, evaluation, safety, and performance measurement

Drive technical standards for platform APIs, service contracts, architecture patterns, and reusable components

Evaluate emerging technologies, frameworks, and vendors in the AI/agentic ecosystem and make strategic recommendations

Mentor engineers and influence cross-functional technical teams through architectural leadership and hands-on guidance

Ensure platform solutions align with enterprise requirements for scalability, resilience, security, and maintainability

Contribute to Vertex’s long-term AI strategy by identifying opportunities to expand platform capabilities and increase enterprise adoption

Required Qualifications

Advanced degree in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or a related technical field; or equivalent combination of education and experience

10 +   years   of   experience designing and building enterprise-grade AI/ML platforms and distributed systems

Deep expertise in agentic AI architectures, LLM-based applications, and platform engineering

Proven experience with retrieval-augmented generation (RAG) systems, vector search, document retrieval, and knowledge integration patterns

Strong experience with AI orchestration frameworks, workflow engines, and multi-step agent execution patterns

Demonstrated experience designing centralized operational platforms for monitoring, governance, observability, and control

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

Experience defining architecture, standards, and reusable services for large-scale enterprise environments

Strong understanding of AI system evaluation, quality measurement, and performance optimization

Experience partnering with cross-functional stakeholders and influencing technical direction across teams

Excellent communication, leadership, and problem-solving skills

Ability to balance strategic architecture leadership with hands-on technical execution

Technical Skills Required

Agentic AI platform architecture

Large Language Models (LLMs)

Retrieval-Augmented Generation (RAG)

AI orchestration and workflow design

Agent monitoring and observability

AI governance, policies, and controls

AI FinOps, token economics, budgeting, cost allocation, consumption forecasting, and model-cost optimization

AI Gateway / Control Tower architecture, including model routing, provider abstraction, fallback, rate limiting, and policy enforcement

Evaluation frameworks for AI systems

Platform engineering and reusable service design

Distributed systems architecture

API and service design

Knowledge retrieval systems

Telemetry, logging, and operational analytics

Scalability, reliability, and performance engineering

Security and enterprise controls for AI platforms

Preferred Skills

Experience building enterprise AI platforms in regulated or highly governed environments

Familiarity with human-in-the-loop workflows and responsible AI practices

Experience implementing policy engines, guardrails, and audit frameworks for AI applications

Knowledge of ML infrastructure, model serving, and production AI operations

Experience with cloud-native architectures and modern DevOps/ MLOps   practices

Exposure to user experience considerations for AI-powered applications and intelligent systems

Ability to translate complex technical capabilities into scalable enterprise adoption strategies

Experience leading technical teams through platform transformation initiatives

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Pay Range:

$188,000 - $282,000

Disclosure Statement:

The range provided is based on what we believe is a reasonable estimate for the base salary pay range for this job at the time of posting. This role is eligible for an annual bonus and annual equity awards. Some roles may also be eligible for overtime pay, in accordance with federal and state requirements. Actual base salary pay will be based on a number of factors, including skills, competencies, experience, and other job-related factors permitted by law.

At Vertex, our Total Rewards offerings also include inclusive market-leading benefits to meet our employees wherever they are in their career, financial, family and wellbeing journey while providing flexibility and resources to support their growth and aspirations.  From medical, dental and vision benefits to generous paid time off (including a week-long company shutdown in the Summer and the Winter), educational assistance programs including student loan repayment, a generous commuting subsidy, matching charitable donations, 401(k) and so much more.

Company Information

Vertex is a global biotechnology company that invests in scientific innovation.

Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at ApplicationAssistance@vrtx.com