{"id":3159008,"url":"https://alion.io/job/mastercard-principal-ai-engineer-4","title":"Principal AI 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":161,"ghost_share":0.019,"stale_share":0.453,"repost_share":0.062,"time_to_fill_p50_days":27,"computed_at":"2026-10-28T05:59:10Z"}},"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":["Gurgaon, India","Vadodara, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":29000,"max_usd":77000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":47},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"RAG","optional":false},{"name":"pySpark","optional":true},{"name":"Python","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-21T00:00:00Z","employer_posted_date":"2026-10-21","last_verified_at":"2026-10-28T09:25:50Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"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\nPrincipal AI EngineerAI 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.Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.\nYou will be joining a team of AI and data engineers working on innovative AI and ML fraud solutions. Our innovative cross-channel AI solutions are applied in Fortune 500 companies in industries such as fin-tech and payments processing. We are pursuing a highly motivated individual with strong problem-solving skills to take on the challenge of structuring and engineering data and cutting-edge AI model evaluation and reporting processes.\nNOTE: This role will be reporting to the VP of AI Engineering for AI Solutions.\nAs a Principal AI Engineer, you will:\nLead the architecture, design, and implementation of enterprise AI and agentic systems, ensuring scalability, reliability, and security.\nBuild and manage AI-ready data products, retrieval pipelines, vector data stores, and knowledge systems that power AI solutions.\nDevelop and standardize agent engineering capabilities, including orchestration, tool integration, memory management, and multi-agent workflows.\nEstablish AI observability, evaluation, and AgenticOps practices, including tracing, monitoring, and performance measurement of AI systems.\nPartner with Data Science, Data Engineering, and Product teams to accelerate the delivery and operationalization of AI solutions across the enterprise.\nAll About You\nDeep expertise in Data Engineering, AI Engineering, or Machine Learning platforms, with a proven track record of delivering production-grade AI solutions at scale.\nStrong understanding of modern AI architectures, including retrieval-augmented generation (RAG), vector databases, agent frameworks, orchestration patterns, and LLM-powered applications.\nExperienced in designing and building scalable data pipelines, data products, APIs, and distributed systems that support AI and analytics workloads.\nDemonstrated technical leadership with the ability to influence architecture decisions, mentor engineers, and drive the adoption of engineering best practices across teams.\nPassionate about solving complex business problems through innovation, with a pragmatic approach to balancing speed, quality, security, and operational\nProven ability to translate emerging AI capabilities into enterprise-scale platforms, reusable services, and measurable business outcomes.\nAt least an undergraduate degree in CS, or a STEM related field\nPrior experience in payment fraud detection modeling\nNice to have:\nPhD/Master’s in CS, Data Science, Machine Learning, AI or a related STEM field\nExperience in with data engineering and model building in PySpark using Spark ML on petabyte scale data\nUnderstands and implements methods to evaluate own work and others for bias, inaccuracy, and error\nLoves working with error-prone, messy, disparate, unstructured data\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 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