The AI Development Engineer – Specialist is responsible for building and integrating AI capabilities into Codebeamer applications, working across both back-end and model integration layers. This role involves hands-on development of AI services, support for model deployment, and close collaboration with product and engineering teams to deliver intelligent, user-facing features. Strong software engineering fundamentals combined with real-world AI project experience are essential.
Key Responsibilities
- Implement AI-driven features and microservices within the Codebeamer ecosystem
- Develop machine learning models or integrate third-party AI/LLM APIs into core application workflows
- Support data preprocessing, experimentation, model evaluation, and deployment tasks
- Apply AI techniques such as NLP, classification, summarization, or anomaly detection to product use cases
- Build and maintain APIs, services, and data processing pipelines for AI functionalities
- Participate in architectural discussions, code reviews, and agile ceremonies
- Collaborate with UX and product teams to create user-friendly AI-powered experiences
- Ensure performance, reliability, and scalability of AI components
Required Qualifications
- Hands-on experience with AI/ML development or integration of AI technologies
- Strong programming skills in Python or Java; exposure to ML libraries such as PyTorch, TensorFlow, or scikit-learn
- Experience working with LLMs, embedding models, vector stores, or AI APIs
- Familiarity with data preparation, model training workflows, and evaluation techniques
- Understanding of software engineering best practices (testing, CI/CD, version control)
- Strong problem-solving and communication skills in English
- Exposure to delivering at least one real AI project (academic, professional, or personal portfolio)
Preferred Qualifications
- Experience with Docker, Kubernetes, or similar environments
- Understanding of MLOps workflows or tools
- Familiarity with RESTful APIs, microservices, and cloud technologies
- Exposure to UI/UX considerations for AI-driven features
- Experience with agile development environments
- Knowledge of how AI concepts can be applied in enterprise-grade systems
