Lead AI Platform Engineer – Advisory Transformation

Mastercard; Dublin; On-site; EUR 110,000 - 150,000; Full time

Job summary

Mastercard seeks a Lead Engineer in Dublin to accelerate AI-enabled advisory platforms. You will translate platform strategy into secure, scalable capabilities, and lead hands-on development of AI services, agent frameworks, and reusable components.

You’ll mentor engineers, collaborate with product, data, and business partners, and help shape architecture while ensuring reliability, security, and governance across enterprise-scale data platforms.

Qualifications

• 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.

Responsibilities

• 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.

Skills

AI engineering

Distributed systems

Leadership without people mgmt

Full-stack / back-end

Architectural design

Code reviews

Cloud data platforms

Data engineering

AI tooling

Education

Bachelor’s degree in Computer Science or equivalent

Tools

AWS EMR

Aurora

Databricks

Snowflake

Job description

Mastercard seeks a Lead Engineer in Dublin to accelerate AI-enabled advisory platforms. You will translate platform strategy into secure, scalable capabilities, and lead hands-on development of AI services, agent frameworks, and reusable components.

You’ll mentor engineers, collaborate with product, data, and business partners, and help shape architecture while ensuring reliability, security, and governance across enterprise-scale data platforms.