AI AGENTIC PYTHON DEVELOPERS

We are seeking a highly skilled AI Engineer to design, develop, and optimize Agentic AI systems, leveraging Python and state-of-the-art AI technologies.
The ideal candidate should have deep experience in LLMs (Large Language Models), multi-modal AI, small language models (SLMs), and autonomous AI agents.
You will play a crucial role in building AI-powered agents that autonomously reason, execute tasks, and interact with humans in complex workflows..
Key Responsibilities.
Design and develop AI-powered autonomous agents that can interact with APIs, databases, and external environments..
Implement LLM-based workflows for real-time decision-making and process automation..
Optimize AI models with small language models (SLMs) and multi-modal architectures to improve efficiency and task execution..
Work with AI frameworks (LangChain, Auto-GPT, BabyAGI, Semantic Kernel) for advanced agentic AI capabilities..
Develop robust AI pipelines integrating with cloud platforms like AWS, Azure, or GCP for scalable AI deployment..
Enhance natural language processing (NLP) and reinforcement learning (RL) capabilities for dynamic AI agent behavior..
Integrate AI agents with APIs, databases, and automation tools, ensuring seamless operation in real-world business applications..
Implement AI safety measures including explainability, fairness, and ethical AI development..
Benchmark AI models for performance and accuracy, fine-tuning large-scale AI deployments for efficiency..
Required Skills & Experience.
Technical Skills:.
Programming.
Strong expertise in Python (including libraries like PyTorch, TensorFlow, JAX, or LangChain)..
AI/ML Models.
Experience with LLMs, SLMs, multi-modal AI, reinforcement learning, and self-learning AI systems..
AI Frameworks.
Hands-on experience with Auto-GPT, BabyAGI, LangChain, Semantic Kernel, and Hugging Face Transformers..
Data Engineering.
Experience working with vector databases (Pinecone, FAISS, Weaviate) and LLM fine-tuning..
Cloud & MLOps.
Experience deploying AI models on AWS, GCP, or Azure using tools like Kubeflow, Docker, and Kubernetes..
API Development.
Proficiency in RESTful APIs, GraphQL, and WebSockets for AI agent integrations..
Agentic AI Architectures.
Strong understanding of multi-agent collaboration, cognitive architectures, and AI-driven workflow automation..
Prompt Engineering & Optimization.
Expertise in LLM tuning, Reinforcement Learning with Human Feedback (RLHF), and AI evaluation metrics..
Preferred Qualifications.
Master’s in Computer Science, Data Science, or related fields..
Experience with autonomous AI agents and self-improving AI models..
Knowledge of zero-shot, few-shot learning, and retrieval-augmented generation (RAG) techniques..
Exposure to ethical AI principles, bias detection, and AI safety methodologies.
Experiencia.
Se requiere Idiomas.
Inglés – Avanzado.
Alemán – Intermedio Jornada.
Completa Horario.
Flexible 40 hours work week Salario.
desde  € anual Sobre FinArc Consulting GmbH.
A cutting-edge AI & Automation Solutions Company specialising in Agentic AI, LLM-powered automation, and intelligent workflow orchestration for enterprises.
The company focuses on building autonomous AI agents that enhance efficiency.