New

Senior AI Engineer

50k - 70k EUR50 000 - 70 000 EUR/ rok./ rok.B2BB2B (netto)

SeniorFull-time·B2B

#380139·Dodano dziś·0

Źródło: nofluffjobs.com

Tech Stack / Keywords

Machine learningAIGoPython

BSc/MSc in Computer Science, Engineering, or a related field.
5+ years of professional experience in backend development using Golang (preferred), Java, or Python.
2+ years of hands-on experience developing and deploying production GenAI applications.
Strong understanding of vector databases and semantic retrieval techniques.
Practical experience with LLMs and prompt engineering, including the use of APIs and tools.
Experience with agentic architectures and AI orchestration frameworks such as LangChain or Genkit.
Solid understanding of the full software development life cycle, including CI/CD pipelines, testing, and deployment on Cloud.
Experience working in cross-functional teams, collaborating with product and program managers.
Experience optimizing, monitoring, and testing LLM-based applications.
Genuine passion for emerging GenAI technologies and innovation in the AI field.
Strong teamwork and collaboration skills with a proactive and solution-oriented mindset.
Commitment to continuous learning.

Design, develop, and maintain intelligent backend systems combining LLMs, retrieval systems, and custom APIs, ensuring high performance, scalability, and reliability.
Participate in team discussions and conduct code reviews, ensuring high standards for GenAI applications’ code quality, security, maintainability, and best practices (testing, CI/CD, observability, documentation).
Stay up to date with generative AI trends by proposing, researching, and integrating new technologies such as vector databases, agent frameworks, and LLM observability tools to enhance AI capabilities.
Collaborate cross-functionally with front-end developers, data scientists, and product managers to define requirements and design and deliver robust end-to-end solutions.
Monitor and improve existing AI systems, identifying opportunities for optimization, cost efficiency, and performance enhancement.

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