• Lead the technical execution of complex AI initiatives, owning the design and delivery of solutions within a product or technical domain while partnering with senior engineers on broader architectural direction. • Design, build, train, evaluate and improve advanced machine learning and LLM-based systems for patient and provider-facing products (e.g., conversational AI, personalization, user understanding, clinical decision support, chronic care management). • Own problems end-to-end: scope the problem with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with the right monitoring and guardrails. • Develop robust evaluation frameworks — offline benchmarks, human-in-the-loop review, online experiments — that give us confidence our models are safe, accurate, and improving over time. • Build and improve the platform that lets the team move quickly: data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers. • Partner closely with clinicians, product, and engineering to translate medical and operational requirements into ML problems and ship measurable improvements to patient and clinician experience. • Set technical direction for your area, mentor other engineers, and raise the bar on engineering and scientific rigor. The scope of leadership scales with seniority. • Stay close to the literature and the rapidly evolving AI ecosystem; bring back what is most useful for our patients and our team.

Principal Engineer, Artificial Intelligence Authoring Location Boston, Massachusetts Employment Type Full-time Work Arrangement Hybrid (Hybrid-Eligible or On-Site Eligible) - Hybrid: Work remotely up to 2 days per week OR - On-Site: Work 5 days per week on-site Salary $166,640–$250,000 annually Job Description: Position Summary: We are seeking a highly skilled and visionary Principal Engineer, AI Authoring to join our AI Authoring Platform team. Reporting to the Director of AI Authoring Platform, you will lead the design, development, and optimization of Vertex’s AI-driven content generation engine. This role is pivotal in shaping the technical architecture of our platform, ensuring the performance, accuracy, and scalability of our LLM-powered authoring tools. You will tackle complex engineering challenges, including automated document workflows and Retrieval-Augmented Generation (RAG)-based architectures, to support the creation of high-quality, compliant, and efficient regulatory documents. Key Duties and Responsibilities - Design and maintain the end-to-end technical architecture for AI-assisted document generation, focusing on modular LLM integration, prompt engineering, and retrieval pipelines, while partnering closely with the AI Architect to ensure alignment with enterprise standards and scalability. - Build and optimize sophisticated Retrieval-Augmented Generation (RAG) systems that accurately pull from vast clinical and regulatory data sources to assist in document creation. - Engineer the data connectors and transformations required to feed structured and unstructured data into AI models for automated document population. - Develop and implement automated testing and validation frameworks to ensure AI-authored outputs meet the strict safety and compliance standards of the Life Sciences industry. - Rapidly prototype new AI authoring features, such as automated summarization or cross-document consistency checks, to determine technical viability before full-scale development. - Serve as the final escalation point for complex technical blockers, from debugging model hallucinations to optimizing cloud infrastructure for high-compute AI workloads. Knowledge and Skills - Proven experience in designing and implementing AI-driven platforms, particularly those leveraging LLMs and RAG architectures. - Expertise in prompt engineering, retrieval pipelines, and modular AI system design. - Strong background in engineering data workflows, including structured and unstructured data integration. - Experience with automated testing and validation frameworks, particularly in regulated industries. - Proficiency in cloud infrastructure optimization for AI workloads. - Exceptional problem-solving skills, with the ability to address complex technical challenges. - Strong collaboration and communication skills to work effectively with cross-functional teams - Familiarity with the Life Sciences industry and its compliance requirements (preferred). - Experience with automated document workflows and AI-based content generation (preferred). Education and Experience - 8+ years of experience in software engineering, with a focus on AI, machine learning, or technical platform development. - Proven track record of leading the design and implementation of AI-driven systems, including LLM-based platforms and RAG architectures. - Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field. - Hands-on experience with cloud platforms (e.g., AWS, Azure, or GCP) and distributed computing systems. - Demonstrated expertise in building and deploying production-grade AI/ML systems in complex, data-intensive environments. - Experience working in regulated industries, such as Life Sciences, is a strong plus. Why Join Us? At Vertex, you will have the opportunity to work on cutting-edge technologies that make a real difference in people’s lives. We offer a collaborative and innovative work environment, competitive compensation, and opportunities for professional growth. If you are passionate about leveraging AI to revolutionize content generation and thrive in solving complex engineering challenges, we encourage you to apply and join our mission to transform lives through innovation. #LI-HYBRID Pay Range: $166,640 - $250,000 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. Flex Designation: Hybrid-Eligible Or On-Site Eligible Flex Eligibility Status: In this Hybrid-Eligible role, you can choose to be designated as: 1. Hybrid: work remotely up to two days per week; or select 2. 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. #LI-Hybrid 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

• Work as a software engineer • Maintain and expand a deep understanding of agentic coding • Design and build agentic coding systems that we can trust to deliver high-quality outputs • Develop a deep understanding of AI application development patterns and techniques, including emerging approaches and architectures. • Take end-to-end ownership of new features, working with other teams to deliver exceptional reliability and a great developer experience. • Work with multiple programming languages: Python and TypeScript, Java, Go. • Serve as a domain expert on AI design patterns, collaborating with field staff to provide best-practices and canonical examples. • Work directly with our developer community to debug issues that need expert attention and get feedback on Temporal features and APIs. • Write public technical documentation describing Temporal concepts and APIs. • Go the extra mile to support a customer in need, on the rare occasion that our teams’ engineering expertise is needed. • Travel to meet your coworkers for a week once or twice a year. • Attend the occasional developer conference to talk about how great Temporal is (optional).

Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone-freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow- helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started. Join us to put AI to work for people. Job Description ServiceNow is looking for a strong software engineer and technical lead with deep software design and architecture skills, strong coding ability, and the technical judgment to build reliable production systems at enterprise scale. ServiceNow's core platform is built on a powerful and highly scaled Java service that supports some of the world's largest enterprise workflows. In this team, we are extending that platform with modern Python and Java microservices that complement the main platform architecture and enable new AI-native capabilities. These services are designed to run in Kubernetes-based environments while integrating deeply with the broader ServiceNow platform. We are focused on production-grade services that bring together enterprise data, AI model integrations, scalable APIs, evaluation workflows, and reliable deployment patterns. You will own the design, development, and operation of containerized backend services running in Kubernetes environments. You will apply strong distributed systems and production reliability judgment to build scalable, maintainable services, and you will lead technical design across ambiguous, high-impact problem spaces. Experience working on AI, GenAI, ML-powered, or data-intensive products will help you be especially successful in this role. Responsibilities - Designing, architecting, and implementing Java and Python microservices deployed on Kubernetes - Designing APIs, service boundaries, data models, and integration patterns for AI-enabled products - Building reliable distributed systems that handle concurrency, queueing, retries, fairness, backpressure, and failure recovery - Integrating frontier AI SDKs such as Anthropic, Google, and OpenAI into production software systems - Applying prompt engineering, structured outputs, model evaluation, and production observability to GenAI use cases - Partnering with research, product, security, and infrastructure teams to ship enterprise-grade services - Raising the engineering bar through architecture reviews, code reviews, mentoring, and technical direction Qualifications To be successful in this role, you have: Required Qualifications - 8+ years of professional software engineering experience, with strong fundamentals in data structures, algorithms, distributed systems, APIs, and backend service design - Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving (including using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact) - Demonstrated experience as a technical lead, Staff Engineer, or equivalent senior individual contributor responsible for architecture, technical direction, code quality, and mentoring - Strong backend engineering skills in Java, Python, or equivalent with hands-on experience designing, building, and operating production services - Hands-on experience building or operating containerized applications deployed in Kubernetes, OpenShift, or similar orchestration environments - Experience designing scalable APIs, asynchronous processing systems, queues, event-driven services, or data-processing pipelines - Familiarity with cloud-native infrastructure, service observability, logging, monitoring, reliability engineering, and production troubleshooting - Ability to make pragmatic architecture decisions across performance, reliability, security, maintainability, and delivery speed - Ability to lead other engineers through code reviews, design reviews, and technical mentorship - Strong communication skills and the ability to partner across product, research, engineering, infrastructure, and security Nice to Have - Prior experience working on AI/ML products, collaborating with research teams, or translating advanced AI/ML capabilities into production software - Knowledge of NLP, search, and knowledge extraction - Experience with multi-modal systems such as document ingestion and processing, image processing, and voice - Working experience with frontier AI SDKs such as Anthropic, Google, or OpenAI - Familiarity with prompt engineering, structured outputs, tool calling, agentic design patterns, Model Context Protocol, or AI-assisted development workflows - Experience with observability tools such as Prometheus, Grafana, Instana, or equivalent monitoring/logging platforms - Knowledge of MLOps or applying machine learning models to production use cases - Experience with infrastructure backends such as PostgreSQL, Redis, Kafka, RabbitMQ, S3-compatible object storage, or equivalent technologies - Published work, patents, conference papers, or open-source contributions related to AI systems, knowledge systems, search, retrieval, or large-scale data processing For positions in this location, we offer a base pay of $166,500 - $291,400, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.