- Company Name
- EUROPEAN DYNAMICS
- Job Title
- AI Engineer
- Job Description
-
**Job Title**
AI Engineer
**Role Summary**
Design, develop, deploy, and maintain AI/ML solutions—including NLP, generative AI, and LLM-based systems—within a service-oriented architecture. Collaborate closely with client IT teams, architect scalable AI solutions, and present technical blueprints to both technical and business stakeholders while ensuring best practices in data management, MLOps, and DevOps.
**Expactations**
- Deliver production‑ready AI components that meet business and technical requirements.
- Maintain high‑quality code, secure deployments, and adhere to ethical and legal AI guidelines.
- Act autonomously in all phases of the AI lifecycle: design, development, testing, documentation, and integration.
**Key Responsibilities**
1. Design and implement AI solutions (NLP, machine learning, generative AI, LLMs).
2. Architect IT infrastructure for AI projects, selecting appropriate models, techniques, and tools.
3. Create and present solution blueprints; moderate workshops and collect stakeholder feedback.
4. Establish and enforce data, master, and metadata management practices; implement MLOps pipelines.
5. Train custom machine‑learning and deep‑learning models on structured and unstructured data.
6. Deploy, scale, and secure AI workloads on AWS or Azure platforms.
7. Build and maintain CI/CD pipelines, containerization (Docker, Kubernetes), and version‑controlled code repositories.
8. Document, test, and integrate AI components into larger service‑oriented architectures.
9. Monitor ethical and legal implications of AI systems in an enterprise context.
**Required Skills**
- Proficiency in Python and key AI/ML/NLP libraries: pandas, scikit‑learn, TensorFlow, PyTorch, Transformers, spaCy, NLTK, OpenAI APIs.
- Deep knowledge of advanced AI techniques: LLMs, generative AI architectures, Retrieval‑Augmented Generation (RAG), agentic workflows (LangChain, CrewAI), function calling, machine‑learning pipelines (MCP).
- Production experience with traditional and modern machine‑learning algorithms.
- Strong data engineering: pipelines, metadata/model versioning, relational SQL, NoSQL (Elasticsearch, MongoDB, Cassandra).
- Cloud expertise in AWS or Azure for AI deployment, scaling, and security.
- DevOps skills: Git workflows, CI/CD, Docker, Kubernetes, agile methodologies.
- Ability to independently develop, test, document, and integrate AI modules.
- Excellent command of the English language.
- Knowledge of AI ethics, privacy, and regulatory considerations is an asset.
**Required Education & Certifications**
- Master’s degree in IT, Computer Science, or a related discipline.
- Minimum nine (9) years of relevant IT experience in AI/ML development.
- (Optional) Relevant certifications such as AWS Certified Machine Learning – Specialty, Azure AI Engineer Associate, or similar.