Artificial Intelligence Engineer

Excelloit Consultancy Services; Deutschland; Remote; EUR 90,000 - 130,000; Full time

Job summary

Excelloit Consultancy Services is seeking an experienced AI Software Engineer to design and deploy ML/AI solutions for real-world business needs. You will build LLM applications using OpenAI/Azure OpenAI/Claude, develop RAG pipelines and embeddings, and implement guardrails for production-grade systems in a fully remote, international setup.

You will collaborate with product teams to translate requirements into scalable AI solutions, ensure observability and security, and contribute to code

Qualifications

• Bachelor’s or Master’s degree in CS/AI/DS/Math or related field.
• 4+ years of professional software engineering experience, incl. 2+ years in production AI/ML.
• Hands-on experience with PyTorch, TensorFlow, scikit-learn, pandas and NumPy.
• Strong experience with LLMs, RAG, embeddings and vector databases.
• Experience with OpenAI, Azure OpenAI, Anthropic Claude or similar models.

Responsibilities

• Develop and deploy ML/AI solutions for real-world business requirements.
• Build LLM applications using OpenAI, Azure OpenAI, Claude, or similar models.
• Develop RAG, embeddings, vector search and re-ranking solutions.
• Create AI agents and agentic workflows with guardrails and evaluation.
• Develop AI/ML pipelines and production-ready services using Python.
• Implement MLOps, CI/CD, monitoring, logging and evaluation practices.
• Deploy AI applications on Azure using Docker and Kubernetes/AKS.
• Manage source code with Git, branching and pull requests; participate in reviews.
• Collaborate with product/business teams to understand requirements and deliver AI solutions.
• Ensure AI systems are secure, reliable, observable, and scalable.

Skills

LLM development

RAG embeddings

Python

Git & code reviews

CI/CD

Docker Kubernetes

Azure OpenAI tooling

OpenAI tooling

Communication skills

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

PyTorch

TensorFlow

scikit-learn

pandas

NumPy

OpenAI / Azure OpenAI

Claude

Cursor/Claude Code

Azure DevOps / GitHub Actions

Docker

Kubernetes

Vector databases

Job description

• Develop and deploy ML and AI solutions for real-world business requirements.
• Build LLM applications using OpenAI, Azure OpenAI, Anthropic Claude, or similar models.
• Develop RAG, embeddings, vector search, and re-ranking solutions.
• Build AI agents and agentic workflows with appropriate guardrails and evaluation.
• Develop AI/ML pipelines and production-ready services using Python.
• Use AI coding tools such as Claude Code and Cursor alongside traditional coding.
• Implement MLOps, CI/CD, monitoring, logging, and evaluation practices.
• Deploy AI applications on Microsoft Azure using Docker and Kubernetes/AKS.
• Manage source code using Git, branching, and pull-request workflows.
• Work with product and business teams to understand requirements and deliver effective AI solutions.
• Ensure AI systems are secure, reliable, observable, and scalable.
• Participate in technical and code reviews and support other engineers.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, Mathematics, Statistics, or a related field.
• 4+ years of professional software engineering experience, including at least 2 years in production AI/ML.
• Experience with PyTorch, TensorFlow, scikit-learn, pandas, and NumPy.
• Hands-on experience with LLMs, RAG, embeddings, and vector databases.
• Experience with OpenAI, Azure OpenAI, Anthropic Claude, or open-source models.
• Experience with Claude Code, Cursor, or similar AI development tools.
• Strong knowledge of Git and code review practices.
• Experience with CI/CD, Azure DevOps, or GitHub Actions.
• Hands-on experience with Microsoft Azure, Docker, and Kubernetes/AKS.
• Strong communication and problem-solving skills.
• Ability to work effectively in a fully remote, international team.

Preferred Experience

• Agentic AI and AI orchestration.
• Prompt engineering and model evaluation.
• Fine-tuning and structured outputs.
• Terraform or Bicep.
• AI observability, monitoring, and MLOps.
• Experience with security, privacy, and responsible AI practices.