Senior Software Engineer (Python, Golang, Kubernetes)

Holisticon Connect is a division within NEXER GROUP, a custom software development company started in Poland in 2017 with a team of over 140 people. The company works with world-renowned brands from Scandinavia, the UK, and Western Europe, focusing on competence growth.

• M.Sc. in Computer Science/Engineering or equivalent industry experience.
• Expert-level production experience with Python.
• Solid hands-on experience with Golang for building and operating services.
• Deep understanding of microservices, distributed systems, and API design (REST/gRPC), focusing on clean contracts and failure modes.
• Practical experience with SQL and NoSQL databases, including schema design and performance tuning.
• Familiarity with object storage solutions (e.g., S3).
• Proven experience deploying and operating services on Kubernetes.
• Strong Unix/Linux fundamentals.
• Practical knowledge of key AWS services (EKS, EC2, S3, RDS, IAM, CloudWatch) and ability to design cost-efficient architectures.
• Strong engineering practices including CI/CD, automated testing, code reviews, documentation, and a security-first mindset.
• Ability to lead technical initiatives, communicate trade-offs clearly, and collaborate across multidisciplinary teams.

Nice to have:

• Experience with ML/AI tooling such as Kubeflow, MLflow, Feast, Argo, Airflow, Ray, and model versioning/monitoring solutions.
• Experience with large-scale image processing or digital pathology data using libraries such as OpenSlide, scikit-image, or OpenCV.
• Experience with performance engineering including concurrency, memory profiling, high-throughput data pipelines, and GPU/accelerator integration.
• Experience working in regulated environments (e.g., GxP), including data governance and privacy requirements.
• Experience with JavaScript/TypeScript for building internal tools and dashboards.
• Experience with event-driven architectures and streaming platforms (e.g., Kafka).

• Take end-to-end ownership of core Python services powering computational pathology and image analysis within Oncology R&D AI.
• Keep services robust, scalable, and well maintained.
• Shape microservice architecture by defining clear service boundaries and interfaces.
• Guide key design decisions.
• Drive improvements in reliability and performance across the platform.