About this role
Capco is shaping the future of financial services by building advanced artificial intelligence, machine learning, and MLOps solutions that solve complex challenges for leading banking and asset management clients. Professionals entering this consultancy operate at the intersection of data science and software engineering, where they design intelligent models, build robust applications, and establish the infrastructure needed to run workloads reliably in production.
Team members tackle diverse initiatives ranging from generative AI and large language models to microservices and automated deployment pipelines, depending on their specific background and expertise. The organization thrives on a collaborative, entrepreneurial culture where engineers and scientists take ownership of their work, challenge existing conventions, and turn ambitious ideas into practical enterprise systems. Ideal candidates bring a strong foundational background in software development or quantitative disciplines, coupled with a genuine curiosity for emerging technologies and a pragmatic approach to problem-solving.
What you will do
- Design, develop, and productionize innovative artificial intelligence and machine learning solutions that address concrete business needs.
- Explore and implement modern approaches spanning machine learning, generative AI, large language models, and intelligent automation.
- Build robust applications and services utilizing Python, application programming interfaces, microservices, and cloud-native technologies.
- Develop reusable libraries, frameworks, and common assets designed to accelerate artificial intelligence adoption at scale.
- Design and maintain end-to-end pipelines that support the complete lifecycle from experimentation through deployment and continuous monitoring.
- Apply modern MLOps, DevOps, and software engineering practices to secure and maintain production-grade systems.
- Collaborate across multidisciplinary teams of engineers, data scientists, architects, and business stakeholders to turn prototypes into reliable solutions.
What you need
- Bring approximately four or more years of professional experience in software engineering, data science, machine learning, MLOps, or a closely related area.
- Hold a university degree in computer science, mathematics, physics, engineering, or another relevant discipline, or possess equivalent practical experience.
- Demonstrate strong problem-solving capabilities alongside a solid understanding of software engineering and application design practices.
- Show practical experience either developing machine learning models, building AI-powered applications, or operating infrastructure and production pipelines.
- Exhibit the ability to work effectively within agile, collaborative team environments.
- Communicate technical ideas clearly and collaborate productively with both technical and non-technical stakeholders.
Nice to have
- Hands-on experience with frameworks and platforms such as LangChain, Haystack, Kubeflow, or comparable technologies.
- Experience designing LLM/RAG architectures, vector search, embeddings, AI agents, or generative AI applications.
- Familiarity with major cloud platforms, cloud-native AI/ML services, microservices architectures, and Kubernetes.
- Knowledge of DevOps, Infrastructure as Code, CI/CD, observability, and production monitoring.
- Experience working within banking, financial services, or other highly regulated industries.
Skills and tech stack
Questions candidates ask
What location is this role based in?
This position is located in Kraków, Poland, operating within the Capco Poland entity.
What is the hiring process for this position?
The recruitment process includes a screening call with the recruiter, a hiring manager interview, a client interview, and subsequent feedback or an offer. The exact process may vary depending on the specific role and project.
What kind of professional background is required?
Candidates need around four or more years of professional experience in software engineering, data science, machine learning, MLOps, AI engineering, or a closely related area. A relevant university degree or equivalent practical experience is also expected.