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Capital Markets, Technology Infrastructure Summer Analyst, Shared Platform Services Team

Job in Jersey City, Hudson County, New Jersey, 07390, USA
Listing for: RBC
Seasonal/Temporary position
Listed on 2026-01-01
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: 2026 Capital Markets, Technology Infrastructure Summer Analyst, Shared Platform Services Team

Job Description What is Tech Infrastructure?

RBC Tech Infrastructure is making some significant technological bets over the coming years. We are investing in innovation, out of the box thinking, and experimentation using the latest tools and platforms in the industry.

We can’t do it alone! We’re looking for individuals with awesome skills who stand out in a crowd. If you’re top of your class, own the hackathon circuit, think big, and are perpetually curious, we want you!

What is the opportunity?

As a Tech Infrastructure Intern, you will join RBC Tech Infrastructure as we automate processes within the bank by delivering enterprise-grade, data-intensive AI and GenAI solutions. You will work alongside your team in a real software development/product engineering environment, making lasting contributions to our Production codebase. You will work daily with subject matter experts, receive technical and professional mentoring, and present your work to your direct team, the larger Tech Infrastructure community and executive leadership.

As a member of the Shared Platform Services (SPS) Team, you will play a critical role in the end-to‑end software development lifecycle (SDLC), from gathering requirements and designing solutions to development, testing, deployment, and knowledge transfer to support teams. This is a unique opportunity to grow your expertise in machine learning infrastructure and work with a passionate, high‑performing team committed to bringing AI and GenAI solutions to enterprise at scale!

What

will you do?
  • Immerse yourself in the team’s business challenges to develop an innovative product.
  • Step outside your comfort zone, bringing your teamwork, communication, and collaboration skills to help your team succeed.
  • Work with cutting edge technology and paradigms to bring a scalable and future‑forward solution to the bank.
  • Design, develop, and implement AI‑enabled data ingestion applications and machine learning systems.
  • Collaborate with peers to write, troubleshoot, enhance, and document high‑quality code aligned with strategic initiatives and detailed requirements.
  • Ensure seamless integration of machine learning applications into enterprise‑grade infrastructure while maintaining high performance and reliability.
  • Implement LLM agents and deploy them on hybrid cloud environment.
  • Partner with internal teams across RBC to deliver software features, resolve issues, and implement bug fixes.
What do you need to succeed? Must have:
  • Pursuing a Bachelor’s, Master’s, or Doctoral Degree with a focus on computer science, engineering, data science, product engineering, or another related field.
  • Entering the final year of a four‑year college or university program or relevant master’s program (candidates should be anticipating graduation in Winter 2026 or Spring 2027).
  • Excellent interpersonal and highly developed communication skills (verbal and written).
  • Creative and analytical thinker who is self‑driven and capable of working in a fast‑paced environment.
  • Proficiency in programming languages such as Python or Java.
  • Experience working with relational databases (e.g., MSSQL, Postgre

    SQL, MySQL).
  • Familiarity with non‑relational databases (e.g., Elasticsearch, Mongo

    DB).
Nice to have:
  • Experience building and maintaining AI and GenAI models.
  • Knowledge of the machine learning application deployment lifecycle, including CI/CD processes.
  • Exposure in deploying to hybrid environments on on‑premise and cloud platforms, including Red Hat Open Shift and Azure.
  • Experience with data analytics and monitoring platforms, such as Splunk, Dynatrace, Moog, PromQL, and Grafana Enterprise Metrics (GEM).
  • Familiarity with machine learning frameworks such as PyTorch, Tensor Flow and/or scikit‑learn.
  • Previous experience with MLOps orchestration tools such as Air Flow, Kube Flow, or Meta Flow.
  • Experience working in agile teams using methodologies like Scrum or Kanban.
What’s in it for you?

We thrive on the challenge to be our best in a team‑oriented, creative environment to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success…

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