• 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.

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director of AI Engineering Overview Mastercard is seeking a Director of AI Engineering to lead a specialised team of AI engineers focused on foundation model development and the delivery of high-value AI use cases. This role is responsible for driving the practical application of transformer-based and generative AI capabilities-ensuring models are effectively developed, adapted, and deployed to solve real business problems. You will lead a team working at the intersection of model development and use case execution, translating foundational AI capabilities into scalable, production-ready solutions. The role requires strong technical judgement, delivery leadership, and the ability to balance innovation with enterprise requirements for reliability, security, and governance. Role In this role, you will lead a team responsible for developing and applying foundation model capabilities to priority use cases. Key responsibilities include: Lead a team of AI engineers focused on foundation model development, fine-tuning, and optimisation, particularly transformer-based and generative AI systems Drive the end-to-end delivery of AI use cases, from problem definition through model integration and production deployment Partner with product and business stakeholders to identify and prioritise high-impact AI use cases, translating them into clear technical execution plans Ensure effective use of foundation models across use cases, including prompting strategies, embeddings, fine-tuning, evaluation, and performance optimisation Collaborate with data engineering and platform teams to ensure data readiness, model integration, and scalable deployment patterns Establish best practices for model evaluation, experimentation, and continuous improvement, ensuring solutions are robust and measurable Embed responsible AI practices, including model validation, bias considerations, and appropriate guardrails Provide technical guidance and coaching to engineers, ensuring high standards in both AI development and software engineering practices Track delivery progress, manage risks, and ensure timely, high-quality execution of use cases aligned to program priorities All About You Proven experience leading teams delivering AI/ML solutions in production, particularly in use-case driven environments Strong hands-on understanding of transformer architectures and generative AI, including fine-tuning, prompting, embeddings, and evaluation Experience bridging model development and real-world application, translating AI capabilities into business impact Solid engineering background, with familiarity in Python, ML frameworks (e.g. PyTorch/TensorFlow), and production deployment patterns Experience working with data engineering and MLOps practices to support training, evaluation, and inference at scale Strong stakeholder management skills, with the ability to align technical delivery to business priorities and measurable outcomes Demonstrated ability to lead and develop high-performing teams, providing technical direction, coaching, and delivery oversight Comfortable operating in a fast-moving, evolving AI landscape with ambiguity and shifting priorities Excellent communication skills, able to articulate complex AI concepts to both technical and non-technical audiences Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: - Abide by Mastercard's security policies and practices; - Ensure the confidentiality and integrity of the information being accessed; - Report any suspected information security violation or breach, and - Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

• As an AI Product Engineer (m/f/d), you combine product thinking, technical understanding, and AI-assisted software development. • You understand customer problems, actively shape solutions, and use AI as a productive development partner — taking full responsibility for quality, architecture, and customer value. • You close the gap between product-oriented, entrepreneurial thinking and technical implementation, bringing solutions from concept to technical realization. • You drive the product’s AI-first evolution, steer the development process, review results, and ensure the right code is written for the right problem. • You create viable solution concepts together with product management and stakeholders — you think in terms of problems and solutions, not tickets. • You guide AI-coding agents such as Claude Code, Cursor, or Codex through the full development process: precise prompts, meaningful task decomposition, and iterative improvement. • You critically evaluate AI-generated code for security, maintainability, performance, and architectural fit, and perform code reviews. • You rapidly build prototypes and MVPs, gather early feedback, and validate assumptions before investing major effort. • You ensure technical quality despite high delivery speed — using tests, acceptance criteria, and CI/CD. • You assess technical feasibility and cost–benefit ratios to provide product management with a solid basis for prioritization decisions. • In addition, you continuously improve our AI-supported development processes and share your knowledge within the team.