{"id":3416938,"url":"https://alion.io/job/mastercard-lead-ai-platform-engineer-3","title":"Lead AI Platform Engineer","company":{"id":252,"name":"Mastercard","domain":"mastercard.com","url":"https://alion.io/company/mastercard","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":87,"open_postings":171,"ghost_share":0.018,"stale_share":0.444,"repost_share":0.058,"time_to_fill_p50_days":27,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States","Boston, United States","Arlington, United States","Atlanta, United States","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":168000,"max":277000,"currency":"USD","period":"year","gross":null,"usd_annual":277000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenShift","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"Docker","optional":true},{"name":"GitOps","optional":true},{"name":"Helm","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-10-28T19:44:24Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-10-29T15:58:17Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Our Purpose\nMastercard 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.\nTitle and Summary\nLead AI Platform EngineerWho is Mastercard?Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we are helping build a sustainable economy where everyone can prosper. We support digital payment choices that make transactions secure, simple, smart, and accessible. Our technology, innovation, partnerships, and networks deliver products and services that help people, businesses, and governments realize their greatest potential.\nOverview\nThe AI Platform Engineering team builds, operates, and evolves Mastercard's enterprise AI platforms. Our mission is to provide scalable, secure, and reliable AI infrastructure that enables teams across Mastercard to accelerate the development and deployment of AI-powered solutions.\nAs a Lead AI Engineer, you will provide technical leadership in designing, implementing, and operating the foundational platforms supporting AI and machine learning workloads across the enterprise. Working at the intersection of platform engineering, cloud infrastructure, MLOps, and AI operations, you will deliver capabilities that enable teams to safely develop, deploy, observe, and scale AI solutions across public and private cloud environments.\nYou will help shape the platforms, tooling, operational practices, and infrastructure supporting the next generation of AI capabilities at Mastercard. You will address complex challenges involving scalability, reliability, observability, governance, automation, and customer enablement while influencing stakeholders and contributing to Mastercard's long-term AI platform direction.\nAbout the Role\nAs a Lead AI Engineer, AI Platform Engineering, you will serve as a developing subject matter expert responsible for advancing the architecture, engineering, automation, and operational excellence of Mastercard's AI platforms. You will lead the technical design and delivery of complex capabilities, improve existing products and processes, and influence decisions across engineering, infrastructure, security, architecture, and governance teams.\nThe ideal candidate combines advanced software engineering and cloud platform expertise with experience supporting production AI and machine learning systems. You are passionate about technical leadership, automation, reliability, and building platforms that empower others to innovate. You are comfortable operating through influence, reviewing technical work, mentoring engineers, and translating complex requirements into scalable solutions.\nResponsibilities\nLead the design, development, and operation of enterprise platforms supporting machine learning, generative AI, agentic AI, and advanced analytics workloads.\nTranslate business, engineering, and operational requirements into scalable platform solutions and implementation approaches.\nDesign and maintain advanced AI and machine learning systems that meet enterprise requirements for security, reliability, availability, scalability, and performance.\nOwn technical delivery across public and private cloud environments, identifying dependencies, resolving complex challenges, and influencing cross-functional decisions.\nBuild and optimize services and workflows that simplify onboarding, development, deployment, operations, and lifecycle management for AI solutions.\nDevelop infrastructure, tooling, and services supporting model training, evaluation, fine-tuning, deployment, inference, monitoring, and governance.\nLead the implementation of repeatable, scalable, and secure MLOps capabilities and AI development workflows.\nBuild and optimize data ingestion, preprocessing, and feature engineering workflows supporting model training and inference.\nDesign observability capabilities including telemetry, performance monitoring, logging, alerting, operational analytics, model monitoring, and drift detection.\nEnsure the operational stability and scalability of AI platforms, driving improvements to reliability, resilience, efficiency, security, and customer experience.\nLead troubleshooting, root cause analysis, and incident response for complex platform issues and translate lessons learned into sustainable improvements.\nInfluence platform architecture through design discussions, reviews, prototypes, tradeoff analysis, and technical recommendations.\nPartner with engineering and product teams to understand requirements, guide solution design, enable adoption, and accelerate delivery of AI-powered products.\nCollaborate with infrastructure, security, architecture, risk, and governance teams to align capabilities with enterprise standards, controls, ethical guidelines, and regulatory requirements.\nEvaluate emerging AI technologies and industry trends and recommend improvements to Mastercard's AI ecosystem and roadmap.\nDrive engineering best practices across Infrastructure as Code, CI/CD, automated testing, secure development, documentation, and operational excellence.\nGuide and mentor engineers through design guidance, technical reviews, problem-solving support, and knowledge sharing.\nAll About You\nRequired Qualifications\nExperience designing, building, and operating cloud-native platforms or large-scale distributed systems in enterprise environments.\nStrong experience delivering solutions across public and private cloud environments.\nExperience deploying and managing containerized workloads using Kubernetes or OpenShift.\nAdvanced software engineering and automation experience using Python.\nExperience leading the technical design and delivery of complex initiatives involving multiple teams or stakeholders.\nExperience implementing CI/CD pipelines, Infrastructure as Code, automated testing, and modern DevOps practices.\nExperience designing or supporting production AI, machine learning, data platforms, or distributed systems.\nStrong understanding of MLOps, model lifecycle management, production inference, and AI system operations.\nExperience implementing telemetry, monitoring, logging, alerting, and operational analytics.\nAbility to diagnose complex issues, lead root cause analysis, and implement sustainable corrective actions.\nAbility to assess architectural options, explain technical tradeoffs, and influence cross-functional decisions.\nAbility to communicate effectively with technical and non-technical stakeholders.\nExperience guiding, mentoring, or reviewing the work of other engineers.\nPreferred Qualifications\nExperience with enterprise generative AI platforms and large language model workloads.\nExperience with model evaluation, fine-tuning, guardrails, responsible AI controls, and model governance.\nExperience with model observability, drift detection, telemetry, and operational analytics.\nExperience with AI serving infrastructure, inference platforms, or AI gateways.\nExperience supporting GPU-based workloads and accelerated computing environments.\nExperience with OpenShift, Kubernetes, Docker, Helm, GitOps, and Infrastructure as Code.\nExperience with enterprise platform engineering, developer enablement, and self-service capabilities.\nFamiliarity with vector databases, retrieval-augmented generation, AI gateways, agentic systems, and model routing.\n• Experience operating in regulated environments requiring strong security, governance, risk management, resiliency, and compliance controls.Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact  and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.\nCorporate Security Responsibility\nAll 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:\nAbide by Mastercard’s security policies and practices;\n\nEnsure the confidentiality and integrity of the information being accessed;\n\nReport any suspected information security violation or breach, and\n\nComplete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.\n\nIn line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance); flexible spending account and health savings account; paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave); 80 hours of Paid Sick and Safe Time, 25 days of vacation time and 5 personal days, pro-rated based on date of hire; 10 annual paid U.S. observed holidays; 401k with a best-in-class company match; deferred compensation for eligible roles; fitness reimbursement or on-site fitness facilities; eligibility for tuition reimbursement; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations.\n\nTHIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 01/26/2027. 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