πWorldwide
Gen Ai Platform Architect

Xebia Poland
πRemote - Worldwide
Please let Xebia Poland know you found this job on JobsCollider. Thanks! π
Summary
Join Xebia, a global leader in digital solutions, and become a key player in designing, developing, and optimizing cutting-edge GenAI products. Leveraging your 7+ years of enterprise architecture expertise and 2+ years of hands-on GenAI experience, you will contribute to mission-critical projects using Python, key GenAI APIs, and cloud infrastructure. You'll work in a Scrum environment, collaborate with a talented team, and stay at the forefront of GenAI advancements. This role requires strong programming skills, extensive cloud experience (AWS preferred), and a work permit within the European Union. Immediate availability is preferred.
Requirements
- Ready to start immediately
- 7+ years in architecture expertise for enterprise builds
- 2+ years of hands-on experience in designing Gen AI solutions
- Strong programming skills in Python and associated GenAI libraries and frameworks
- Strong knowledge of Generative AI technologies, including key APIs (AWS Bedrock, Azure OpenAI, OpenAI) and LLM frameworks (LangChain, LlamaIndex)
- Extensive experience with cloud infrastructure for AI/GenAI/ML on AWS
- Experience with containerization and orchestration technologies (Kubernetes, Docker)
- Work from the European Union region and a work permit are required
Responsibilities
- Designing, developing, and optimizing GenAI based products and solutions
- Preparing documentation of all designs and development
- Working in Scrum, attending Agile ceremonies and presenting the development work incrementally
- Contributing to mission-critical projects by utilizing backlog items and priorities set by the Product Owner
- Staying at the forefront of developments in GenAI
- Sharing insights and best practices within your team and across the organization to foster innovation and drive results
Preferred Qualifications
- Experience with LLM guardrails, security, and monitoring
- Expertise in LLM testing and evaluation frameworks
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