AI Software Engineer Intern — AI-Powered Test Case Generator

Lombard Odier Group

Genf

On-site

CHF 20,000 - 27,000

Full time

14 days+

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Job summary

Lombard Odier Group in Geneva invites a Master's student in Computer Science or Software Engineering to join as an Internship – AI Software Engineer. You will help build AI-powered tooling to analyze code and generate regression-test scenarios for securities settlement systems.

Work alongside engineers to explore LLM approaches, tackle legacy Java apps, and implement prototypes that enhance testing and quality across mission-critical financial software.

Qualifications

  • Master's student in CS/SE or related field, pursuing an internship.
  • Solid foundation in software engineering and algorithms.
  • Interest in financial systems and enterprise-scale apps.

Responsibilities

  • Develop AI-powered solutions to analyze code and generate test scenarios.
  • Explore LLM-based approaches for code understanding and test design.
  • Analyze Java and legacy applications supporting securities settlement.
  • Identify critical business workflows for automated testing coverage.
  • Build prototypes combining AI with software engineering best practices.
  • Improve test coverage visibility with automated reporting.
  • Integrate generated outputs into existing testing frameworks and workflows.
  • Collaborate with engineers and architects to assess AI-driven testing scalability.

Skills

Software engineering foundations
Java programming
LLMs / Generative AI
Distributed systems
Analytical problem solving
Codebase navigation
Team collaboration
Autonomy & curiosity

Education

Master's degree student in Computer Science or Software Engineering

Job description

Lombard Odier Group in Geneva invites a Master's student in Computer Science or Software Engineering to join as an Internship – AI Software Engineer. You will help build AI-powered tooling to analyze code and generate regression-test scenarios for securities settlement systems.

Work alongside engineers to explore LLM approaches, tackle legacy Java apps, and implement prototypes that enhance testing and quality across mission-critical financial software.

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