Mid-Level Backend Engineer with LLM Expertise @

4 days ago


Remote, Czech Republic DEV12 GROUP Full time
Must Have Skills
  • LLM Expertise: At least 2 years of hands-on experience working with large language models (LLMs), including practical experience with Langchain and Langgraph for orchestrating LLM workflows and integrating models into backend systems.
  • Prompt Engineering: Expertise in designing, testing, and optimizing prompts to enhance LLM performance for specific tasks.
  • Backend Development: At least 2 years of experience with FastAPI (Python) or Node.js (JavaScript/TypeScript).
  • Cloud Infrastructure: Strong experience in designing and implementing secure, scalable, and reliable cloud architectures on Azure, GCP, or AWS, ensuring the safety and performance of applications.
  • Database Knowledge: Expertise in working with relational databases like PostgreSQL, MySQL and SQLite.
  • Data Science/Engineering: Ability to clean and analyze large datasets to ensure their quality and relevance for machine learning tasks.
  • Ownership & Initiative: Willingness to own LLM-related tasks and projects, working collaboratively with the tech lead and team.
Nice to Have Skills
  • Advanced LLM Frameworks: Familiarity with advanced LLM frameworks such as Hugging Face Transformers or other production-ready language model libraries and tools used for fine-tuning, model deployment, and natural language processing.
  • On-Premise LLM Development: Experience working with on-premise or self-hosted LLM models, including fine-tuning, managing infrastructure, and optimization.
  • PyCharm: Familiarity with using PyCharm as an integrated development environment (IDE) for Python-based development.
  • TensorFlow: Experience with TensorFlow for building and deploying machine learning models, particularly in relation to LLMs or data science tasks.
  • Machine Learning: Solid understanding of machine learning techniques, model training, and AI pipelines.
  • Front-End Knowledge: Familiarity with front-end frameworks like React (even if you focus mainly on backend).
  • Full-Stack Experience: Experience or interest in full-stack development, contributing both to front-end and back-end features in an agile environment.
    • Impactful Work: You'll have the chance to influence the architecture and AI strategy from day one.
    • Collaboration & Growth: Learn from a tech lead skilled in AI agents and collaborate with front-end devs on meaningful projects.
    • Professional Development: Grow your knowledge of large language models, data science, and cloud-based ecosystems.

Other Perks: flexible working hours, remote-friendly policies

,[Backend Development: Build, maintain, and scale backend systems using FastAPI or Node.js., Cloud Infrastructure: Deploy and manage services on Azure, GCP, and AWS to optimize scalability and performance., Data Engineering: Clean and process large datasets, ensuring high-quality data for LLM models., LLM Integration: Contribute to the development of LLM-driven sales data analysis solutions by optimizing prompt engineering and integrating Langchain and Langgraph frameworks., AI Agent Development: Collaborate with the team to develop AI agents that power advanced language model applications., LLM-focused Projects: Own smaller LLM-related tasks, such as prompt tuning, model optimization, and integrating new LLM features into applications., Collaboration & Mentorship: Work alongside the tech lead to build and maintain state-of-the-art AI models, contributing to both backend and LLM-specific development.] Requirements: Python, Machine Learning, NLP, API, REST API, GraphQL, Cloud, GCP, AWS, Azure, Cloud platform, PyTorch, TensorFlow, Docker, Kubernetes, CD pipelines, AI, Azure ML, Autoscaling, MLOps, MLflow, Kubeflow Additionally: International projects, Flat structure, Small teams.

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