2027 Technology Graduate Programme - AI-Native Data Platform Engineering
TD BankDublin · Posted 4h ago
Location: Dublin, Ireland
Work Location: Dublin, Ireland
Hours: 35
Line of Business: Technology Solutions
Base Pay Details: 50,000 - 50,000 EUR
TD is committed to providing fair and competitive total compensation opportunities to all colleagues. Total compensation is inclusive of the base pay details listed above and opportunity for a variable compensation award specific to this role. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.
As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.
Job Description:
2027 Technology Graduate Programme - AI-Native Data Platform Engineering
TD Securities are offering an exceptional opportunity to join a diverse and dynamic team through our 12-month Technology Internship on the AI-Native Data Platform Engineering team.
From your first day on the TDS Graduate Programme, you will contribute as part of a global team at one of the world’s largest banking institutions. Our development programme offers structured training, exposure to meaningful projects, and opportunities to build the knowledge and skills needed for a career in financial markets. You will gain practical experience on projects that support the team and develop a foundation for your future career within a global organisation.
Internship Overview
Contract Type: Full-time, 12-Month Graduate Programme
Dates: July 2027
Location: Dublin Office: 1 Molesworth Street
Candidates must have an unrestricted right to work in Ireland throughout the entire duration of the internship.
Team Overview:
The TDS Data Platform Engineering team is building the next generation of data platforms where data products, AI agents, and self-service analytics work together to help users discover, understand, and consume data more effectively.
Our mission is to provide a scalable, secure, and AI-ready data platform that empowers domain teams to build and own data products while enabling consumers to interact with data through modern experiences such as AI agents, natural language interfaces, and intelligent automation.
As a Graduate Analyst or a 6-month Intern, you will help shape how AI and data platforms converge. You will work on technologies such as Large Language Models (LLMs), Agentic AI, Model Context Protocol (MCP), data products, APIs, cloud-native platforms, and analytics solutions. You will collaborate with domain owners, data engineers, application teams, and platform engineers to create innovative solutions that make data easier to discover, understand, and use.
We are a highly collaborative team that values curiosity, experimentation, continuous learning, and delivering business value through simple, scalable, and user-centric solutions.
How you will Contribute:
Help design and build AI-ready data platform capabilities that enable self-service data discovery and usage.
Develop AI agents and MCP-based integrations that allow users to interact with data products using natural language.
Collaborate with domain owners to understand their data products and create intelligent experiences that simplify data consumption.
Build APIs, services, and automation frameworks that expose data and business capabilities to AI agents and applications.
Contribute to the development of Retrieval-Augmented Generation (RAG) solutions using enterprise data sources.
Assist in building and maintaining scalable data pipelines and cloud-native data services.
Create proof-of-concepts exploring emerging technologies in AI, data engineering, and developer productivity.
Partner with platform users to understand pain points and improve platform usability and adoption.
Develop tools that help users discover datasets, understand lineage, definitions, ownership, and usage patterns.
Support the implementation of governance, security, and access controls for AI-enabled solutions.
Participate in platform monitoring, troubleshooting, testing, and continuous improvement activities.
Contribute to technical documentation, architecture reviews, and knowledge-sharing initiatives.
Apply engineering best practices including clean code, automated testing, CI/CD, and secure software development.
Continuously research emerging AI and data technologies and evaluate their relevance to the platform.
Key Technologies:
The successful graduate will gain experience in:
AI Agents, Agentic Workflows, and Model Context Protocol (MCP)
Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Prompt Engineering
Java (Spring Boot) for APIs and backend services
Python for data engineering, automation, analytics, and AI solutions
Apache Spark and Dremio for large-scale data processing and data products
Azure Data Platform Ecosystem including Databricks, AKS, ADLS, ADF, and Azure AI Services
Vector Databases and Semantic Search technologies
REST APIs, gRPC, and Event-Driven Architectures
Kafka for real-time data movement
GitHub, GitHub Actions, Jira, and Confluence
Observability platforms such as Dynatrace and Datadog
Security, Governance, and Data Catalog technologies
Who we are looking for:
Recent graduate (2026) or upcoming 2027 graduate with a Bachelors or Masters degree in Computer Science, Software Engineering, Data Engineering, Artificial Intelligence, or a related field.
Passion for solving business problems using data and AI.
Strong curiosity and willingness to explore emerging technologies.
Excellent communication and collaboration skills.
Comfortable working in a fast-paced environment with
What they are looking for
Details
- Work type
- Onsite
- Compensation
- Paid
- Remote eligible
- No
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