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
Managing Consultant, Strategy and Transformation - Generative AI Engineer / Generative AI Data Scientist
Advisors & Consulting Services
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. 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.
The Advisors & Consulting Services group has five specializations: Strategy & Transformation, Performance Analytics, Business Experimentation, Marketing, and Program Management. Our Strategy & Transformation consultants lead clients through impactful decision-making as they tackle strategic, tactical, operational, and transformational business challenges. They apply a broad set of problem-solving techniques to improve the client’s overall strategy, performance, and operations.
Job Summary
We are seeking a Technical Consultant who combines strong hands-on GenAI engineering capability with solid data analytics and data science foundations, and the mindset of a trusted consultant.
This is an experienced individual contributor role where you will design, build, and deploy production-grade Generative AI solutions for enterprise clients, while also contributing to broader data analytics and data science initiatives where GenAI is not always the right answer. You will operate at the intersection of advanced AI engineering, analytical problem-solving, and client advisory, translating ambiguous business problems into scalable, measurable solutions.
You will be expected to contribute and take increasing ownership across the end-to-end delivery: from shaping the problem with stakeholders, to building and productionizing systems, to supporting adoption and handover – with support from senior team members where needed. The ideal candidate is comfortable switching between LLM-centric systems and classical analytics/modelling and can communicate confidently with both technical and non-technical audiences.
Key Responsibilities:
1. End-to-End GenAI Solution Delivery
- Lead the design, development, and deployment of Generative AI solutions using LLMs, Agentic Designs and Multi-Agent Systems taking full ownership of delivery outcomes, timelines, and quality.
- Translate business problems into well-architected GenAI systems that deliver clear, measurable value.
2. GenAI System Architecture & Engineering
- Design and implement scalable GenAI systems, including Retrieval-Augmented Generation (RAG) pipelines, vector database integrations, and API-driven architectures.
- Design systems that balance performance, cost, security, and maintainability in enterprise environments.
4. Productionalization & LLMOps
- Establish CI/CD pipelines and operational practices for GenAI solutions, ensuring reliability, observability, and cost efficiency.
- Work within cloud-native environments to deploy and monitor production AI systems.
5. Data Analytics & Data Science Contribution
- Support broader analytics and data science initiatives, including exploratory analysis, descriptive and diagnostic analytics, and predictive modeling where required.
- Apply sound statistical and analytical judgment to complement GenAI-driven approaches.
6. Rapid Prototyping & Storytelling
- Build interactive demos and lightweight applications to validate ideas, gather stakeholder feedback, and accelerate decision-making.
- Clearly communicate technical concepts, trade-offs, and insights to non-technical stakeholders.
7. Consulting & Stakeholder Engagement
- Act as a trusted advisor to clients and internal teams, helping shape problem statements, success metrics, and solution approaches.
- Collaborate effectively across multidisciplinary teams and contribute to a high standard of consulting delivery.
8. Documentation & Handover
- Produce clear technical documentation and ensure smooth handover of solutions to permanent teams or client owners.
Required Qualifications & Skills
Experience
- 4–7 years of professional experience in software engineering, data science, or applied machine learning.
- At least 2 years of hands-on experience building and deploying Generative AI or LLM-based solutions in real-world environments.
Core GenAI Expertise
- Practical experience working with major LLMs (e.g. GPT, Claude, Llama) via APIs and open-source frameworks.
- Proven experience designing and optimizing RAG systems using tools
such as LangChain or LlamaIndex.
- (Preferred) Understanding of fine-tuning, prompt engineering, and evaluation techniques, including their trade-offs.
Data Analytics & Data Science
- Strong ability to analyze large datasets and synthesize insights using Python and modern analytics libraries.
- Experience with descriptive analytics, business intelligence, and applied modeling to inform decision-making.
- Solid understanding of metrics, benchmarking, and measurement in complex business contexts.
Technical Proficiency
- Advanced Python proficiency and experience with relevant ML/AI libraries.
- (Preferred) Experience with vector databases (e.g. Pinecone, Chroma, Milvus) and embedding models.
- (Preferred) Hands-on experience deploying solutions on cloud platforms (AWS, Azure, or GCP), including managed AI services.
- (Preferred) Experience building prototypes and simple UIs using tools such as Streamlit, Gradio, Flask, or FastAPI. Front-end frameworks (React, Vue) are a plus.
Consulting & Delivery Mindset
- Proven ability to work directly with clients or senior stakeholders.
- Strong sense of ownership, autonomy, and accountability for delivery outcomes.
- Excellent communication skills, with the ability to explain complex ideas clearly and pragmatically.
Education
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field (preferred).
This role is not a research-only position, and it is not limited to prompt engineering or experimentation. You will be expected to build production-ready systems and engage directly with business stakeholders.
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.
