Associate Managing Consultant, Advisors & Consulting Services, GenAI Engineer (12 months fixed term)

Join to apply for the Associate Managing Consultant, Advisors & Consulting Services, GenAI Engineer (12 months fixed term) role at Mastercard . 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 Associate Managing Consultant, Advisors & Consulting Services, GenAI Engineer (12 months fixed term) Overview 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 strategic advisory and execution services, leveraging expertise, data-driven insights, and GenAI-enabled delivery to accelerate innovation and growth. Our Advisors & Consulting Services team combines traditional management consulting with Mastercard’s rich data assets, proprietary platforms, and technologies to provide clients with powerful strategic insights and recommendations. Our teams work with a diverse global customer base across industries, from banking and payments to retail and restaurants. Job Summary We are seeking a highly skilled and motivated Generative AI Engineer for a 12-month contract engagement. This project-focused role is centered on leveraging Large Language Models (LLMs) and other generative technologies to design, build, and deploy a specific set of transformative applications, including pioneering work in agentic commerce. You will be responsible for driving the technical execution of key GenAI initiatives throughout the project lifecycle, from backend model development to creating intuitive user-facing prototypes. The ideal candidate is a self‑directed expert who can deliver high‑quality, production‑ready systems within a defined timeframe. Roles and Responsibilities End‑to‑End GenAI Solution Delivery: Take ownership of the design, development, and deployment of sophisticated applications using LLMs, with a clear focus on meeting project milestones and deliverables. System Architecture & Implementation: Architect and implement robust and scalable GenAI systems for the duration of the project. Key tasks include building Retrieval‑Augmented Generation (RAG) pipelines, integrating vector databases, and managing APIs. Agentic System Development: Develop and refine autonomous agents and multi‑agent systems to automate complex processes and meet specific project objectives. Productionalization & Optimization (LLMOps): Establish and manage CI/CD pipelines for the GenAI applications, ensuring they are performant, cost‑effective, and reliable throughout the contract period. Rapid Prototyping & Demonstration: Build interactive web applications and demos to showcase the capabilities of GenAI models to stakeholders, gather feedback, and validate solutions quickly. Stakeholder Collaboration: Work effectively with internal teams to understand project requirements, provide expert consultation, demonstrate progress, and ensure the final solution meets business goals. Documentation & Handover: Create clear technical documentation and facilitate a smooth handover of the developed systems and processes to the full‑time team at the conclusion of the contract. Qualifications Experience: 4‑6 years of professional software engineering experience, with at least 2 years of dedicated, hands‑on experience building and deploying solutions using Generative AI and LLMs. Core GenAI Expertise: Demonstrable experience with major LLMs (e.g., GPT series, Claude, Llama) via APIs and open‑source libraries like Hugging Face; proven ability to build and optimize Retrieval‑Augmented Generation (RAG) systems using frameworks like LangChain or LlamaIndex; hands‑on experience with model fine‑tuning techniques and understanding of their trade‑offs. Technical Proficiency: Deep proficiency in Python and relevant AI/ML libraries; strong experience with API development and integration (e.g., RESTful APIs, FastAPI); experience with vector databases (e.g., Pinecone, Chroma, Milvus) and embedding models; solid understanding of cloud platforms (AWS or Azure) and deploying AI applications using services like AWS SageMaker or Azure AI; knowledge of containerization technologies (Docker, Kubernetes); prototyping & visualization experience building demos and simple UIs using frameworks like Streamlit, Gradio, or Flask/FastAPI; experience with modern frontend frameworks (React, Vue) is a significant plus. Project Delivery & Autonomy: Results‑oriented professional with strong ownership and ability to work independently, managing time effectively to meet project deadlines. Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field preferred. Language: Ability to communicate effectively in English and Mandarin. Eligibility: Eligible to work in the country where applying and able to travel as required. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks come with an inherent risk to the organization. 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 confidentiality and integrity of accessed information; report any suspected information security violation or breach; complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. J-18808-Ljbffr

Location: Singapore, Singapore, SG

Posted Date: 11/4/2025