What AI Development Jobs are in Ireland?

Description
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help.
You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Amazon Web Services provides a highly reliable, scalable, and low-cost cloud platform that powers thousands of businesses in over 190 countries. AWS' Infrastructure Supply Chain & Procurement organization works to deliver solutions to source, build and maintain our socially responsible data center supply chains. We are a team of highly-motivated, engaged, and responsive professionals who enable the core sustainable infrastructure of AWS. Come join our team and be a part of history as we deliver results for the largest cloud services company on Earth!
The IPS Procurement Category Management Org is responsible for the procurement of all third party provided services required for the operation of our Data Center infrastructure globally, including Colo and Edge facilities for externally delivered services not provided by the facility owner. The team is responsible for the identification, onboarding and performance management of suppliers as well as developing category strategies, conducting competitive tendering processes, supplier negotiations and the preparation of associated Work Orders.
The team is structured into three regions, each led by a regional manager, with each regional team composed of category managers with responsibility for the management of specific areas of spend within the region and a cohort of procurement specialists who support the category managers. The category management approach facilitates a strategic approach to procurement by facilitating in depth market analysis coupled with a cross functional approach to identify supplier and associated contracting options which are focused on meeting the particular needs of the business. Category management moves beyond traditional transactional based purchasing negotiations to provide a strategic approach to longer term, sustainable cost reductions, reducing risk and increasing resiliency in the supply base and facilitating innovation from within the supply base that the business can leverage.
While cost reduction will always be a key focus of the team, the principle cynosure of the team is the delivery of services that are keenly focused on increasing reliability and supporting enhanced availability through robust relationships which support continuity of operations. As service and quality levels can vary greatly, principally based on the skill set within a supplier local organization, the regional structure facilitates tailoring of category strategies to meet local market considerations and closely monitor supplier performance at the local level.
Key job responsibilities
The ideal candidate thinks long term, drives multiple initiatives, and communicates appropriately and influences customers and suppliers at all levels. You must be collaborative, but also work with significant autonomy. To be successful in this role you must be highly analytical; think strategically and globally; have a sense of urgency to meet customer timelines; exhibit curiosity and learning drive; succeed in a fast-paced environment; engage and influence key stakeholders; and have a high level of customer focus and business judgement. Also, you must have a demonstrated track record of managing multiple projects and driving them to completion to meet business objectives. It will be critical to embrace and model Amazon's Leadership Principles and have an entrepreneurial spirit with a "get it done" mentality.
- Manage a complex category within the Maintenance, Repair, and Operation (MRO) domains.
- Achieve cost savings through bidding and negotiations, drive collaboration to achieve long term value delivery.
- Obtain market intelligence, analyze category data and metrics to drive Procurement category strategies.
- Understand trends in customers' needs and concerns, across categories and regions, to influence customers' priorities.
- Lead supplier selection process across multiple sub-categories, internal teams, and regions, and create longer-term supplier selection strategies for management.
- Ensure you are knowledgeable about the supply market, new innovations and supplier capabilities, technically and geographically.
- Ensure you are knowledgeable about sustainability, diversity, in-country value and have experience developing category strategies to incorporate same.
- Develop mechanisms and metrics to track supplier performance related to delivery, quality, and cost.
- Create supplier scorecards to measure and track supplier performance.
- Lead business reviews to discuss best practices and issues and to ultimately improve supplier performance and strengthen business partnerships.
- Innovate within the procurement space, automating and/or improving tools or processes to better support the Procurement Lifecycle.
- Provide support throughout the contracting process, as well as SRM and management of contracts post-execution.
Travel required both domestically and internationally
About the team
AWS Infrastructure Services (AIS)
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help.
You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE), inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Basic Qualifications
- 5+ years of procurement, supply chain, inventory management, contract management, lease administration or operations experience
- 5+ years of relevant strategic sourcing including vendor negotiations, global contract management, process improvement, operational and financial analysis experience
- Experience in strategic sourcing including vendor negotiations, global contract management, process improvement, operational and financial analysis
- Experience with data analysis tools such as Advanced Excel, SQL, Tableau, Python
- Experience in global supply chain management, managing cross-functional teams in a fast-paced consumer electronics product company
Preferred Qualifications
- 4+ years of program, project, product management, or leading a product implementation process experience
- Master's degree in Business Administration, Finance, Economics, Computer Science, or a related field
- Experience in program, project, product management, or leading a product implementation process
- Experience in data centers, infrastructure service providers, or related technology companies
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( ) to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

**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**
AI Engineer 2
Overview
Mastercard is seeking an AI Engineer II to support the development and deployment of AI solutions that power strategic initiatives within the AI & Data organization. This role provides an opportunity to work on advanced AI technologies, including transformer-based and generative AI models, while contributing to the delivery of scalable, production-ready solutions.
Working closely with Senior, Lead, and Principal AI Engineers, you will help develop, evaluate, and operationalize AI capabilities that address real business challenges. This is a hands-on engineering role focused on building technical expertise, delivering high-quality solutions, and growing into greater levels of ownership and technical leadership.
Role
In this role, you will contribute to the development, testing, and deployment of AI and machine learning solutions across the program.
Key responsibilities include:
Develop and support AI and machine learning models under the guidance of senior team members
Contribute to the development and evaluation of transformer-based and generative AI solutions, including embeddings, tokenization, fine-tuning, and inference workflows
Build and maintain components of data preparation, feature engineering, and model training pipelines
Assist in creating and managing datasets required for model training, validation, and evaluation
Support the implementation and optimization of machine learning workflows and model-serving solutions
Help integrate AI models into applications, APIs, and production environments
Support model testing, validation, monitoring, and performance analysis to ensure quality and reliability
Apply established software engineering and MLOps best practices, including version control, testing, documentation, and deployment automation
Collaborate with AI engineers, data engineers, software engineers, and product teams to implement AI solutions
Troubleshoot issues related to model performance, data quality, and system functionality
Participate in code reviews, technical discussions, and knowledge-sharing activities
Stay current with emerging AI technologies, frameworks, and engineering best practices
All About You
2-5 years of experience in AI engineering, machine learning engineering, data science, software engineering, or a related technical field
Strong programming skills in Python
Experience using AI/ML frameworks such as PyTorch, TensorFlow, or similar technologies
Foundational understanding of machine learning, deep learning, and AI engineering concepts
Familiarity with transformer architectures, large language models, tokenization techniques, embeddings, and generative AI technologies
Experience working with data processing, feature engineering, and model training workflows
Familiarity with model evaluation techniques and performance measurement
Exposure to cloud-based development environments such as AWS, Azure, or GCP
Understanding of software engineering fundamentals, including testing, version control, CI/CD principles, and code quality practices
Familiarity with APIs and integrating machine learning models into applications is a plus
Knowledge of data structures, algorithms, and scalable computing concepts
Strong analytical and problem-solving skills
Effective communication and collaboration skills, with the ability to work in a cross-functional team environment
Demonstrated ability to learn new technologies quickly and adapt to evolving technical requirements
Bachelor's degree or equivalent practical experience in Computer Science, Engineering, Data Science, Mathematics, or a related field
**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.

My client is looking for a Senior AI Solutions Engineer with a minimum of 5 years of experience to join their organisation in Limerick. This is a permanent role. Key Skills & Experience 5+ years' experience in AI Engineering, Machine Learning Engineering, Applied Data Science, or a similar technical role delivering production-ready AI solutions. Strong experience developing and deploying machine learning models within manufacturing, industrial, IoT, or operational technology environments, including exposure to MES, SCADA, or sensor data. Proficiency with Python machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn, with experience deploying solutions across AWS, Azure, or Google Cloud. Practical experience building Generative AI solutions, including Retrieval-Augmented Generation (RAG), vector databases, prompt engineering, AI agents, and LLM integration. Solid understanding of MLOps principles, including CI/CD, Docker, Kubernetes, model deployment, monitoring, governance, and lifecycle management. Excellent problem-solving and stakeholder engagement skills, with the ability to translate business requirements into scalable AI and machine learning solutions. Responsibilities Design, develop, and deploy machine learning models that support predictive maintenance, quality inspection, anomaly detection, computer vision, and operational optimisation. Build and maintain end-to-end AI and machine learning pipelines, covering data preparation, feature engineering, model training, deployment, monitoring, and continuous improvement. Develop Generative AI applications using structured and unstructured data, including technical documentation, maintenance records, operational data, and knowledge repositories. Implement robust model governance, monitoring, and evaluation processes to ensure accuracy, performance, explainability, compliance, and long-term reliability. Partner with engineering, manufacturing, operations, and technology teams to identify opportunities where AI can improve efficiency, productivity, and business performance. Contribute to the organisation's AI strategy by promoting best practices, supporting technical standards, and driving continuous innovation across machine learning and AI capabilities.

**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**
Specialist Product Manager - AI
Overview: In virtually every country worldwide, Micro, Small, and Medium Businesses (SMEs) are the lifeblood of economic vitality. Mastercard is dedicated to enabling businesses to survive and thrive stronger than before. Our rallying cry is Empowering Every Business Everywhere. This segment is central to Mastercard's growth strategy - not only because of their global impact but also because of SMEs' significant role in the payment ecosystem as both payers and acceptors of electronic payments.
We are seeking an experienced Specialist Product Manager - AI to drive the strategy, development, and commercialization of AI-powered products within our platform. This role will lead end-to-end product ownership for intelligent agentic solutions, translating complex data, AI/ML capabilities, and partner ecosystems into scalable, high-impact customer-experiences.
Responsibilities:
Own and deliver one or more product features or problem areas within AI-powered solutions, aligned to the broader product roadmap
Translate product requirements into well-defined EPICs, user stories, and acceptance criteria for engineering and data teams
Support the development of LLM-powered and agentic AI features, including conversational experiences and workflow automation
Partner with engineering, design, and data science teams to execute on roadmap commitments, ensuring timely and high-quality delivery
Collaborate on product discovery activities, including user research, hypothesis validation, and experimentation
Oversee and steer the product development process, ensuring compliance with budget, scope, and project timelines.
Communicate effectively with technical and non-technical audiences.
Qualifications:
Solid experience as a Product Manager in a technology-driven environment; exposure to AI/ML products is preferred
Working knowledge of AI concepts such as LLMs, RAG, agentic workflows, and evaluation frameworks
Demonstrated ability to translate product requirements into execution-ready deliverables
Strong problem-solving skills and willingness to think outside the box.
Excellent teamwork skills with an ability to get the work done with minimal supervision.
Advanced degree in Computer Science, AI, Machine Learning, or related field is highly desirable.
Proven track record of managing all aspects of a successful product throughout its lifecycle.
Globally distributed teams in India, EU and US. Some travel may be required.
Additional Information:
This role is hybrid, with the expectation of working in the Dublin office at least 3 days per week.
**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.

Mission Statement We connect patients, providers, and caregivers to the right care, at the right time, in the right place, resulting in exceptional experiences and outcomes for patients and providers Our vision is to be the partner of choice for healthcare organizations in the delivery of patient access solutions The Specific behaviors and skills we care about most are Integrity, innovation, Collaboration, Empathy and Excellence. Summary The Technical Lead AI Enablement & Automation is the senior technical owner for AI-enablement and automation delivery. The role takes solution concepts and solution designs set by the Principal and, where in place, the Solution Architect and owns how they are built, tested, secured and delivered into live Operations. The role turns ideas into detailed technical designs, leads the build team, confirms feasibility, manages technical trade-offs and ensures solutions work beyond the demo environment. The primary delivery lane is digital front door and automation, including Genesys-enabled automation, Architect flows, bot flows, conversational AI, workflow automation, data actions, API integrations, partner tooling and structured data capture. The role also provides technical delivery leadership across Agent Augmentation, Quality & Conversation Intelligence and Insights & Analytics where there are Genesys, automation, integration or structured-data dependencies. Essential Functions Take solution designs from the Principal and Solution Architect and turn them into detailed, buildable technical designs and delivery plans. Confirm technical feasibility, refine integration and configuration approaches, and flag where a design must change to be deliverable. Define technical build patterns for Genesys, Architect flows, bot flows, data actions, APIs, partner tooling and cloud services. Lead the automation build team across design, configuration, integration, testing, documentation and release. Personally design, prototype or troubleshoot critical components where senior technical input is needed. Be hands-on in build during the early phase while the team and standards are being established. Work with the Principal to assess emerging AI-enabled go-to-market concepts and determine what is technically feasible. Provide early technical input into solution packaging, delivery effort, integration complexity, dependencies and sequencing. Help ensure new propositions are designed in a way that can actually be built, supported and scaled. Lead, mentor and set technical standards for the build team, including the Contact Centre Automation Engineer and junior technical / enablement resources. Set standards for testing, version control, documentation, peer review, security, naming conventions and supportability. Allocate and sequence build work against delivery priorities and dependencies. Review technical outputs for quality, completeness, maintainability and alignment to design intent. Experience and qualifications Significant hands-on experience in contact-centre technology, digital operations, automation, conversational AI, workflow automation or comparable technical delivery environments. Strong hands-on experience with Genesys Cloud or equivalent contact-centre platforms, including flows, data actions, integrations, APIs and digital / automation capability. Experience leading or mentoring technical builders, developers, engineers or automation specialists. Ability to take a solution design or business outcome and deliver it end-to-end into a live, regulated environment. Comfortable operating with ambiguity and able to work out a deliverable technical approach without waiting for perfect requirements. Experience working with external technology vendors and internal stakeholders on technical delivery. Knowledge of the contact-centre industry operating models, technology landscape and delivery practices is a strong advantage. Understanding of US healthcare particularly patient access HIPAA, PHI, GDPR or regulated operational environments is a strong advantage. Experience with agent assist, conversational AI, bot flows, automated QA, conversation intelligence, digital front door or structured-data capture is advantageous. Ireland based, with willingness to work US hours and overlap with US teams, clients and delivery activity. Reporting structure? Principal Operational Advancement and Performance Improvement Location: Ireland. Skills: Leader AI Leading

Engineering Lead | AI Startup | Remote (Ireland) Location: Remote (Ireland) Competitive Salary + Equity + Benefits Build the next phase of an AI product already trusted by global enterprise customers. We're partnering with a well-funded Irish AI startup entering one of the most exciting stages of its journey. Having recently secured fresh funding, the business is scaling rapidly and preparing for its next major milestone, with plans to raise a Series A over the coming year. They're already delivering AI solutions to some of the world's largest enterprise organisations and are looking for an Engineering Lead to help shape the next chapter of the company. This is an opportunity to join while the team is still small enough for your work to have a genuine impact. The Opportunity This isn't a traditional management position. The current technical leader is wearing multiple hats across product, architecture, engineering leadership and customer delivery. They're looking for someone they trust to take ownership of the engineering team while remaining heavily involved in building the product. You'll spend roughly half your time writing code and solving technical challenges, with the other half focused on mentoring engineers, improving engineering practices, contributing to architecture and helping the team deliver at pace. They're equally open to speaking with: An experienced Engineering Lead or Tech Lead from a startup or scale-up. A Senior Software Engineer who's already mentoring others and is ready to step into their first leadership position. What You'll Be Doing Lead and mentor a small engineering team. Support and develop junior and mid-level engineers. Run stand-ups, sprint planning and retrospectives. Remove blockers and keep engineering delivery moving. Contribute to technical architecture and solution design. Continue writing production code as part of the engineering team. Improve engineering standards, SDLC and code review processes. Work closely with product and technical leadership on roadmap delivery. Help shape how engineering scales as the company grows. Tech Stack Current technologies include: Python PHP / Laravel React Google Cloud Platform (GCP) Experience across every technology isn't essential. They're looking for engineers with broad technical knowledge, strong problem-solving skills and experience delivering products within startup or scale-up environments. What They're Looking For You'll likely bring: Experience as either a Senior Software Engineer ready to step up or an existing Engineering Lead / Tech Lead within a start up or scale up in Ireland. Strong backend engineering experience. Experience mentoring or leading engineers. Exposure to any cloud platform. Excellent communication skills. Confidence making technical decisions with limited direction. A product mindset and genuine ownership mentality. Why Join? This is one of those opportunities where timing really matters. You'll be joining: A recently funded Irish AI company. A business preparing for significant growth and a future Series A. A genuinely collaborative engineering culture with very little bureaucracy. A product solving complex real-world problems using AI. A team where your technical decisions will directly influence the future of the platform. An environment where ideas are encouraged and ownership is expected. If you're someone who enjoys building products, solving difficult engineering problems and helping grow teams, you'll feel right at home. Package Competitive Salary Equity Healthcare Pension Home office budget Fully remote within Ireland Flexible working environment Opportunity to join at a pivotal stage of growth The process has been designed to move quickly: If you're curious to learn more, apply today or reach out for a confidential conversation. How to Apply To apply for this role, submit your CV via the application form provided. Alternatively, to speak in absolute confidence about this opportunity, please contact Jack Tyrrell via Disclaimer If you have a disability which means you require assistance at any stage of the recruitment process, please contact us directly to discuss. We are committed to providing equality of opportunity to all. Please note, we are receiving an exceptionally high number of applications at present and will be unable to shortlist candidates who are not meeting the specific requirements for this role. Due to the high volume of applications, we may be unable to provide individual feedback. We thank you in advance for your understanding. Benefits: Work From Home equity

**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**
Lead DevOps Engineer - AI & Data (Foundation Models)
Overview
Mastercard is seeking a DevOps Engineer to support a strategic AI engineering team focused on foundation model development and AI use case delivery. This role is responsible for enabling reliable, scalable, and automated deployment of AI systems-ensuring models and supporting services can move efficiently from development to production.
You will work closely with AI engineers, data engineers, and software engineers to build and maintain the CI/CD pipelines, cloud infrastructure, and runtime environments required to support production AI workloads. This role is critical in ensuring that AI solutions are delivered with strong standards for reliability, security, and operational excellence.
Role
In this role, you will be responsible for building and operating the infrastructure and deployment pipelines that enable AI systems at scale.
Key responsibilities include:
Design and maintain CI/CD pipelines for AI and data workloads, supporting model training, testing, and deployment
Automate build, deployment, and release processes across environments, ensuring consistency and reliability
Manage and optimise cloud infrastructure (primarily AWS, with flexibility across cloud platforms) to support AI and data workloads
Support deployment and operation of AI models, including inference services, batch jobs, and data pipelines
Collaborate with data and AI engineers to streamline development-to-production workflows, reducing friction and cycle time
Implement monitoring, logging, and alerting to ensure system observability and rapid issue resolution
Ensure systems are designed for high availability, resilience, and performance
Embed security best practices into deployment pipelines, including secrets management, access control, and secure configuration
Support Databricks environments and workflows where applicable, including job orchestration and integration with data pipelines
Contribute to troubleshooting production issues and participating in incident response and post‑incident improvements
Promote DevOps best practices, including infrastructure as code, automation, and continuous improvement
All About You
5-8 years of experience in a DevOps, platform engineering, or similar role supporting production systems
Strong experience building and maintaining CI/CD pipelines in production environments
Hands‑on experience with cloud platforms, particularly AWS (experience with Azure or GCP also valuable)
Experience with infrastructure as code tools (e.g. Terraform, CloudFormation, or similar)
Familiarity with containerisation and orchestration (e.g. Docker, Kubernetes)
Experience supporting data and AI workloads, including model deployment pipelines, batch processing, or streaming jobs
Working knowledge of monitoring and observability tools (e.g. logging, metrics, tracing)
Experience with Databricks or similar data platforms is a strong plus
Strong understanding of software delivery practices, version control, and automated testing
Familiarity with security best practices in cloud and CI/CD environments (e.g. secrets management, IAM, least privilege access)
Strong problem‑solving skills and ability to work in a collaborative, fast‑moving environment
Clear communicator, able to work effectively with engineering, data, and platform teams
**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.

**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**
Senior AI Engineer - Foundation Models and Transformers-1
Overview
Mastercard is seeking a Senior AI Engineer to design, build, and deploy high‑quality AI solutions that support key business and product initiatives. This role is hands‑on and delivery‑focused, contributing directly to the development of production AI systems while collaborating closely with product, data, and engineering partners.
As a Senior AI Engineer, you will work on well‑scoped AI initiatives, applying advanced machine learning and software engineering practices to move models from experimentation into reliable, performant production systems. This role represents a critical technical contributor level, with opportunities to grow toward technical leadership and broader system ownership.
Role
In this role, you will be responsible for building and operationalizing AI solutions under the guidance of Lead and Principal engineers.
Key responsibilities include:
Design, develop, and deploy AI and machine learning models to solve defined business and product problems
Contribute to the development and optimization of transformer‑based and generative AI models, including fine‑tuning, evaluation, and inference workflows
Build and maintain data pipelines, feature engineering logic, and training workflows in collaboration with data engineering teams
Implement model serving and inference solutions, integrating models into downstream applications and APIs
Apply MLOps best practices, including experiment tracking, versioning, automated testing, monitoring, and model performance evaluation
Participate in code reviews, design discussions, and technical planning to ensure high‑quality, maintainable solutions
Collaborate with product managers and stakeholders to translate requirements into technical implementations
Support troubleshooting and performance tuning of models and AI systems in production environments
Continuously improve technical skills and stay current with advances in AI, ML frameworks, and engineering practices
All About You
Solid experience developing machine learning or AI solutions and deploying them into production environments
Strong proficiency in Python and experience with ML frameworks such as PyTorch and/or TensorFlow
Hands‑on experience with transformer‑based models (e.g. BERT‑style encoders, generative models, embeddings, or similar architectures)
Experience working with data pipelines and datasets, including data preparation, feature engineering, and training data management
Familiarity with cloud platforms (AWS, Azure, or GCP) and cloud‑based ML tooling
Working knowledge of MLOps practices, including model deployment, monitoring, and lifecycle management
Strong software engineering fundamentals, including version control, testing, and code quality practices
Ability to collaborate effectively within cross‑functional teams and follow established architectural and engineering standards
Clear communicator with a growth mindset and interest in progressing toward broader technical ownership
Bachelor's degree or equivalent practical experience in computer science, engineering, data science, or a related field
**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.