Lead, Software Engineer

Lead, Software Engineer

Who is Mastercard?
Mastercard is a global technology company in the payments industry, building digital platforms that securely power commerce at global scale. Our technology enables innovation across financial services, data, AI, and digital experiences, while maintaining the highest standards of reliability, security, and trust.
Business & Market Insights (B&MI) is Mastercard’s data, analytics, and intelligence organization, responsible for transforming vast global data assets into actionable insights and decision-support products for customers across industries. B&MI builds platforms and products that move beyond static analytics, embedding AI, advanced modelling, and increasingly agentic systems directly into customer workflows. Product, engineering, and data teams work together to deliver secure, governed, production-ready intelligence solutions that drive measurable business outcomes.
Role Summary
We are looking for a Lead Engineer within our Advisors & Transformation group to help accelerate the transformation of consulting through AI and technology. Working closely with business, product, AI, data, and engineering partners, the Lead Engineer will translate platform strategy and architecture into secure, scalable, production-ready capabilities.
This is a hands-on technical lead role with also potential to lead a team of engineers either internally or vendor team. You will lead the design and delivery of reusable services, integrations, workflows, and developer capabilities for an AI platform that improves productivity across the consulting organization and supports the commercialization of AI-enabled consulting solutions.
You will help scale tools such as Claude, Copilot, and Cowork; implement agent orchestration and integration layers; extend AI knowledge-base capabilities; contribute to FinOps and TokenOps practices; and make reusable AI patterns, skills, and agents easier for engineering and consulting teams to adopt.
Roles and Responsibilities
As a Lead Software Engineer, you will:
• Lead hands on development of AI, agentic systems and support of scalable, reusable AI platform capabilities.
• Help integrate large language models, AI services, agent frameworks, workflow engines, knowledge bases, and orchestration platforms.
• Turn target-state architecture and product priorities into clear technical designs, delivery plans, and working solutions.
• Provide day-to-day technical direction to junior engineers and vendors teams, reviewing code while maintaining accountability for delivery quality.
• Build and integrate APIs, services, event-driven workflows, data pipelines, agent workflows, and user-facing platform capabilities.
• Partner with product, business, architecture, and engineering teams to refine requirements, identify dependencies, and deliver incremental value.
• Support migration of existing components toward the future-state architecture while maintaining operational continuity.
• Contribute to AI frameworks and agent workflows.
• Identify technical risks early, challenge assumptions constructively, and recommend pragmatic trade-offs across build, buy, partner, and reuse options.
• Mentor junior engineers, help strengthen engineering practices, and promote a culture of quality, collaboration, inclusion, and continuous learning.
• Ensure solutions align with Mastercard technology standards and expectations for architecture, security, privacy, compliance, reliability, and scale.
Required Skills and Experience
We are seeking an experienced Lead Engineer who combines strong software engineering fundamentals with hands-on technical leadership and a passion for applied AI, transformation, and business impact.
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• Strong experience as a hands on AI engineer
• Experience with large scale data platforms and modern ML/AI tooling
• Previous experience building AI platform in Advisory, Consultancy space a distinct advantage
• Experience building or integrating solutions that use LLMs, AI services, agent frameworks, workflow engines, orchestration platforms, vector search, retrieval-augmented generation, or related capabilities.
• Understanding of GenAI and agentic workflows, including prompt design, grounding, tool use, evaluation, guardrails, monitoring, and responsible AI considerations.
• Familiarity with cloud and data technologies such as AWS EMR, Aurora, Databricks, and Snowflake, or comparable platforms used for data-intensive applications.
• Solid foundations in software engineering, system design, and distributed systems
• Professional experience building and operating distributed, production-grade software systems, including substantial full-stack or back-end engineering experience in an agile delivery environment.
• Strong object-oriented design and programming skills, with a track record of creating reusable, maintainable, and scalable components.
• Experience leading technical delivery for a team or workstream, including design reviews, code reviews, engineering planning, mentoring, and production readiness.
• Ability to influence technical direction without formal people management responsibility
• Strong technical judgement and the ability to evaluate trade-offs across architecture, security, scalability, integration, cost, delivery speed, and operational support.
• Clear written and verbal communication skills, with the ability to explain technical decisions to engineering, product, business, and governance stakeholders.
• Ability to coordinate across teams, locations, and vendors while maintaining momentum, transparency, and delivery discipline.
• A collaborative mindset, a commitment to engineering excellence, and enthusiasm for AI and emerging technologies.

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.