- Location
- Geneva, Geneva, Switzerland; Zug, Zug, Switzerland · Geneva, Geneva, Switzerland
- Type
- Internship
- Department
- Research & Technology (Internship)
- Seniority
- Internship
- Experience
- 22+ years
- Education
- Bachelor
- Source
- Greenhouse
Description
Garda Capital Partners (Garda) is a multi-billion dollar alternative investment firm with over 22 years of experience deploying relative value strategies across fixed income markets for institutional investors. We hire, grow, and mentor great talent and remain steadfast in our commitment to building a culture that helps them succeed. Garda is more than a workplace. We are built on trust, integrity, and a shared vision for how we work together, the enduring relationships we build, and the consistency of our results. Garda's primary offices are located in Wayzata, New York City, West Palm Beach, Geneva, Zug, Copenhagen, Singapore, and Scottsdale.
Garda is seeking a Software Engineer Intern (AI Internal Tools) for a 6-month internship, who will report to the AI Lead. The role focuses on building and improving internal systems, tools, and engineering infrastructure that let teams across Garda use AI effectively, safely, and reliably.
This is a hands-on engineering position spanning internal applications, integrations, shared AI platform components, evaluation tooling, observability, and developer workflows — contributing to both new features and existing production systems. It is not model training, quant research, or one-off prototyping; the focus is on maintainable, reusable systems for broad internal use.
Ideal candidates are strong technical students who thrive on ambiguity, pick up new technologies quickly, and take ownership of code quality. While AI-assisted development tools are used, the intern is expected to apply solid engineering judgment, test rigorously, and deliver secure, maintainable work.
Position Responsibilities
- Build and improve internal applications, backend services, APIs, and integrations that bring AI capabilities into firm workflows.
- Contribute to shared AI platform capabilities, such as gateway services, access and identity integrations, monitoring, observability, and support tooling.
- Deliver small, production-minded features and services, including design, implementation, testing, documentation, deployment support, and iterative improvement after release.
- Help evaluate AI models, tools, and internal AI applications; contribute to practical evaluation methods, benchmarks, monitoring, and feedback loops.
- Identify recurring needs and generalizable patterns in work across teams, then help turn them into reusable components, standards, or automation rather than one-off solutions.
- Work with engineers, infrastructure, security, compliance, and internal users to understand requirements, navigate dependencies, and incorporate feedback into robust solutions.
- Use AI-assisted development tools effectively while maintaining ownership of code quality, correctness, security, reliability, and maintainability.
- Support and improve existing systems by investigating issues, improving documentation, and helping make services easier to operate and support.
Qualifications & Desired Skills
- Pursuing a Bachelor's in Computer Science, Engineering, Mathematics, or Quantitative Finance
- Demonstrated software-development experience through coursework, internships, personal projects, open-source work, or similar practical experience.
- Proficiency in at least one programming language and the ability and interest to learn the languages, frameworks, and tools required for the work.
- Strong software-engineering fundamentals, including data structures, algorithms, debugging, testing, version control, and clear code design.
- Interest in building backend services, APIs, internal applications, integrations, or developer/infrastructure tooling.
- Sound problem-solving skills and good judgment about trade-offs among speed, quality, reliability, and maintainability.
- Comfort working in a changing environment, clarifying ambiguous requirements, and iterating constructively with stakeholders.
- Clear written and verbal communication skills; able to collaborate with both technical and non-technical colleagues.
- Interest in practical AI systems and AI-enabled development. Prior experience with a particular AI platform, programming language, or cloud technology is welcome but not required.
- Interest in financial markets or investment management is a plus, but is not required.
