AI Software Solutions Engineer

3 days ago


Warszawa Poznań, Czech Republic beBee Careers Full time

The role of an AI Software Solutions Engineer requires a deep understanding of designing and implementing cloud-native architectures, integrating Large Language Models (LLMs), multimodal models, and Retrieval-Augmented Generation (RAG) pipelines. This individual will work closely with Agile teams to design and implement AI systems that meet architectural standards and adhere to AI governance guidelines.

The ideal candidate will have expertise in AWS and Azure cloud services, containerization (Docker, Kubernetes), orchestration, and Infrastructure as Code (IaC) tools (Terraform, CloudFormation). Additionally, they will have experience in designing and deploying large-scale, cloud-based AI applications, including vector databases, SQL, NoSQL, and data storage solutions.

This position involves architecting solutions that integrate GenAI capabilities into enterprise systems while ensuring seamless interoperability with backend services, APIs, databases, and user interfaces. The candidate must be able to define robust patterns for utilizing LLMs, multimodal models, and RAG and agentic systems, as well as design efficient model-serving pipelines.

The AI Software Solutions Engineer will ensure that AI applications follow software engineering best practices, including version control, Continuous Integration/Continuous Deployment (CI/CD), automated testing, and code quality assurance. They will also architect secure and scalable APIs to facilitate seamless communication between AI models, databases, and user interfaces.

Key responsibilities include:

  • Designing end-to-end system architectures integrating AI and non-AI components
  • Architecting solutions that integrate GenAI capabilities into enterprise systems
  • Defining robust patterns for utilizing LLMs, multimodal models, and RAG and agentic systems
  • Designing efficient model-serving pipelines
  • Ensuring adherence to cloud-native best practices across AWS and Azure deployments

In addition to technical skills, the successful candidate will possess strong communication and collaboration skills, with the ability to provide technical leadership in AI architecture reviews, design discussions, and solution validation.



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