Informacje o stanowisku

About BlueSoft:

At BlueSoft, we are a team of engineers and technology experts dedicated to solving real business problems using cutting-edge technology. We specialize in AI-driven solutions, cloud optimization, application modernization, and software development to help businesses transform and grow. If you’re passionate about cloud technologies and want to work in a forward-thinking company where you can make a genuine impact, we’d love to hear from you.

Position Overview:

We’re seeking a Python Developer with a strong background in working with Large Language Models (LLMs), Data Science , and agentic AI frameworks. In this role, you’ll design and build prototypes, experiment with novel approaches to business processes, and deliver AI-driven solutions that bring real value to our clients. You’ll collaborate with cross-functional teams, from data scientists and ML engineers to product strategists, ensuring that our AI solutions not only push the technological envelope but also solve tangible business problems.

Key Responsibilities:

Prototyping & Experimentation:

Rapidly build and iterate on prototypes leveraging LLMs, vector databases, and knowledge graphs to explore new AI-driven capabilities.

Agentic Solution Development:  Design and implement autonomous agents using frameworks such as LangGraph, CrewAI, … , integrating reasoning steps, planning capabilities, and tool usage.

Data Analysis and Categorization:  Utilize data science algorithms for data categorization, clustering, and analysis. Perform graph analysis to understand data relationships and leverage community detection algorithms like Leiden for insights.

RAG Integration:  Develop retrieval-augmented generation workflows and document retrieval to enhance context relevance. Use various approaches to RAG (GraphRag, AgenticRAG, …)

Prompt Engineering:  Craft, refine, and iterate complex prompts to elicit high-quality outputs from LLMs. Using different prompting techniques to achieve the best business results.

NLP & ML Operations:  Work closely with ML engineers and data scientists to fine-tune models, create embeddings, and optimize prompts for performance, accuracy, and cost-effectiveness.

Scalable & Maintainable Code:  Write clean, modular, and testable Python code, ensuring high reliability, maintainability, and performance of deployed solutions.

Collaboration:  Partner with cross-functional teams—including DevOps, AI researchers, and customer success—to understand requirements, guide technical decision-making, and translate client needs into working solutions.

Continuous Improvement:  Stay current with the rapidly evolving LLM and NLP ecosystem, experiment with new approaches, and continuously refine our internal tooling and best practices.

What We’re Looking For:

Experience:

Core Engineering: 3+ years of experience in Python development, with strong knowledge of best practices, code structure, and testing frameworks.

LLM & NLP Expertise:  Hands-on experience working with large language models (e.g., GPT-4, Claude, LlaMA …) and a solid understanding of prompt engineering, embedding techniques, and fine-tuning.

Agentic Frameworks:  Familiarity with building agent-based AI solutions using frameworks like LangChain, CrewAI, … , including chain-of-thought reasoning, action planning, and tool orchestration.

Data Science & Analysis:  Proven ability to apply data science algorithms for categorization, clustering, and graph analysis. Experience with community detection methods such as Leiden algorithm for network analysis and insight extraction.

Vector Databases & Knowledge Graphs:  Experience integrating vector databases and knowledge graphs into RAG pipelines, optimizing search and retrieval for improved model context.

ML Tooling:  Comfortable working with libraries like Hugging Face Transformers, sentence-transformers, and related NLP tooling.

Language Skills:  Strong command of English (B2+ level or above), with excellent written and verbal communication abilities.

Additional Skills (Nice to Have):

Cloud & DevOps:  Basic knowledge of cloud platforms (AWS, Azure, GCP), containerization (Docker), and CI/CD pipelines.

Business Acumen:  Ability to connect technical capabilities to business value and communicate these insights clearly to non-technical stakeholders.

Model Training Background:  Experience or familiarity with training machine learning models, including fine-tuning pre-trained models for specific tasks.

Language Skills:  Knowledge of German

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