Jobs / Canada / Mastercard International Incorporated
Senior AI Engineer
Mastercard International Incorporated · 🇨🇦 Vancouver, Canada
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereNo government sponsor record covers this employer in this country.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeCanada has no single salary bar: the employer usually needs a positive LMIA. Pay at or above the provincial median wage + 20% (e.g. C$36.92/h in Ontario) puts it in the high-wage stream. Source: https://www.canada.ca/en/employment-social-development/services/foreign-workers/median-wage.html, rules effective 2026-07-17.
- Confirmed live todayWhen a source last listed this job as open.
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Sponsor Radar — Mastercard International Incorporated
No government sponsor record covers this employer in this country.
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About the role
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 Overview: AI Solutions, part of Mastercard’s AI & Data organization, scales AI across the enterprise, moving use cases beyond pilots into trusted, production-grade capabilities embedded in Mastercard’s platforms and products. Centralizing this capability drives speed to scale, operational resilience, consistent delivery standards, and responsible AI by design, in close partnership with the AI Center of Excellence. This position sits on the Horizontal Enablement team, reporting to the Manager, AI Engineering who heads the Tooling and Agent Development remit. The remit builds the internal tooling and agentic systems that make AI development faster and more repeatable across Mastercard and works alongside data science teams to move their research products into production. As a Senior AI Engineer, you will independently build and ship agent-based applications and developer tooling, and partner with data science counterparts and engineering partners to take proofs of concept from experiment to deployable solution. About the Role: • Independently execute key elements of projects within AI Engineering, resolving problems and roadblocks as they arise. • Design and build agentic systems and internal tooling, including agent orchestration, tool and API integration, memory and context handling, prompt and workflow design, evaluation harnesses, and guardrails for safe and reliable behavior. • Contribute to the design and development of scalable AI and machine learning systems that address complex business needs, adhering to engineering best practices. • Work with data science counterparts to understand their research products and translate proofs of concept into deployable solutions, then liaise with engineering partners to carry those solutions through to production. • Implement models into production, designing scalable training pipelines and deployment frameworks. • Conduct hyperparameter tuning and validation to meet targeted performance metrics, ensuring robustness and efficiency. • Monitor model and agent performance, manage versioning, and update solutions to sustain high-quality outputs. • Ensure the operational stability and scalability of AI systems, adhering to ethical guidelines and contributing to the organization’s AI infrastructure. • Contribute to solution development for new tools and services and lead smaller projects as an experienced individual contributor with specialized knowledge. All About You: • Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field; equivalent practical experience considered. • Hands-on experience building agentic systems in production or near-production settings, including agent frameworks, tool and API integration, multi-step workflows, evaluation, and guardrails. • Practical experience with Generative AI and LLMs, including prompt design, RAG patterns, and model selection and evaluation trade-offs. • Experience partnering with data scientists or researchers to productionize proofs of concept and working with engineering partners to deliver them. • Proficiency in Python and SQL, with solid software engineering fundamentals in testing, version control, packaging, and code review. • Exper