Junior AI Developer

Implement AI-driven solutions for international clients, with a strong focus on LLMs, agentic architectures and data-centric engineering.
Develop and integrate Python-based backend components that interact with LLM APIs and local/on-premise models.
Build and maintain RAG pipelines, vector databases and retrieval logic.
Implement integrations with external systems, internal APIs and AI model endpoints.
Design and develop agent-based architectures and orchestrations for complex workflows.
Work with Docker and Docker Compose to create reproducible development and production environments.
Collaborate directly with clients, architects and other developers as an active member of an agile project team.

At least 1 year of commercial experience as a software developer (or relevant hands-on experience in AI/ML/LLM engineering).
Strong knowledge of Python 3 (OOP, functional programming, modular code design, clean code principles).
Good command of SQL and experience working with relational databases.
Practical experience integrating with LLM APIs (OpenAI, Azure OpenAI, Ollama, Hugging Face, Anthropic, etc.).
Understanding and hands-on experience with prompt engineering techniques.
Practical experience building or modifying RAG pipelines (document preprocessing, retrieval tuning, chunking strategies, embeddings).
Familiarity with vector databases (e.g., Qdrant, Pinecone, pgvector).
Understanding of agent-based architectures (multi-agent workflows, tool usage, Orchestrators, ReAct patterns).
Knowledge of Docker and Docker Compose.
Experience working with Git (branching strategies, PR reviews, CI/CD basics).
Fluency in English (B2/C1 level at least).
Availability to work full-time and ability to work in the European Union.

Experience with frameworks such as LangChain, LangGraph, Haystack or similar agent/RAG frameworks.
Knowledge of graph databases (especially Neo4j).
Experience with ML libraries: Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch.
Hands-on experience running open-source LLMs locally using tools such as Ollama, vLLM or Text Generation Inference.
Familiarity with MLOps/LLMOps concepts (logging, tracing, experiment tracking, Langfuse).
Exposure to modern cloud platforms (Azure, AWS, GCP) and AI-related services.
Demonstrated ability to learn quickly and a strong interest in emerging AI technologies.

Flexible working hours and a hybrid home office model (2-3 times per week in the office) as work-life balance is crucial at Sollers.
A chance to be promoted twice a year and a clearly defined career path with salary forecast.
Opportunities for growth with a training budget that you can use for courses and conferences. We also provide access to an online training platform and co-fund language classes.
An internal coach to guide you through the onboarding, further training and career opportunities, plus a budget to be used for your lunches together.
A chance to #domore for the planet and the community as part of Sollers Change Makers – our volunteering program.
Lots of teambuilding activities, trips, hobby groups and cultural events to create a company powered by teamwork.
Probably all the benefits you can think of!

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