Senior Software Engineer for AI projects - job 1 of 2

As a Senior Software Engineer for AI projects at Capco, your primary responsibilities include delivering functional AI applications and data pipelines, integrating AI models into existing systems, building and integrating CI/CD practices, and optimizing data processing. You'll also work with cloud-based solutions that enhance our services in the financial sector.

To qualify for the Senior Software Engineer for AI projects at Capco, you should possess a minimum of 5 years of work experience specifically in software development focusing on AI. You should be proficient in either Python or Java and should also have good command of SQL. Familiarity with CI/CD technologies and cloud platforms like GCP, Azure, or AWS is essential, along with an advanced level of both English and German.

Working as a Senior Software Engineer for AI projects at Capco offers a plethora of benefits. You will receive private healthcare, 25 vacation days a year, and a cafeteria contribution of 50 EUR monthly. Additionally, you will have access to training programs and certification courses, a flexible home office policy, and various wellness activities that promote work-life balance.

Capco is committed to the growth of its employees, particularly for the Senior Software Engineer for AI projects role. You will benefit from extensive technical and soft skills training, professional certifications, and full access to platforms like Udemy for continuous learning. Plus, you’ll have a personal coach to guide you through your career journey!

The recruitment process for the Senior Software Engineer for AI projects role at Capco consists of several steps. Initially, you'll have a screening call with a recruiter, followed by a technical and competencies interview with a seasoned Capco colleague, after which you’ll receive feedback and an offer. The process is designed to ensure that you and Capco are a perfect match.

In your response, emphasize specific projects where you've integrated AI into financial applications. Highlight the technologies and methodologies you used and how your solutions improved efficiency or decision-making in a financial context.

Discuss your understanding of continuous integration and continuous deployment. Share experiences from past projects, explaining how you implemented automation and improved the development cycle, and mention any tools you've used to facilitate CI/CD.

Detail your proficiency in either Python or Java, providing examples of projects where you utilized these languages. Illustrate how your knowledge benefitted the project outcomes, particularly in the context of AI development.

In your explanation, define Infrastructure as Code and describe any specific tools or frameworks you’ve used, such as Terraform or CloudFormation. Provide examples of how IaC has streamlined deployment and resource management in your past projects.

Talk about the techniques and technologies you utilize to ensure scalability, such as microservices architecture or managed cloud services. Highlight any challenges faced in previous roles and how you overcame them to achieve optimal performance.

Share consistent approaches you've developed for debugging, including tools you rely on (like logging frameworks or debuggers), and any methodologies like test-driven development that help you catch issues early.

Explain your continuous learning strategy, whether it's through attending seminars, completing online courses, or contributing to open-source projects. Mention any specific resources like blogs, forums, or networks that you actively engage with.

Provide a detailed account of a particularly challenging AI project, the role you played, the obstacles encountered, and how your contributions led to a successful outcome. Discuss measurable impacts, like performance improvements or cost reductions.

Discuss your time management techniques and tools you use to prioritize tasks, such as Agile methodologies, Kanban boards, or project management software. Illustrate with an example where this approach benefitted the project timelines.

Mention the specific cloud platforms you are familiar with, such as GCP, Azure, or AWS. Provide examples of how you've deployed applications or integrated services in the cloud, including any cost-saving measures or performance optimizations you implemented.