- Company Name
- Black Pen Recruitment
- Job Title
- AI Engineer (Information Technology/Software)
- Job Description
-
Job Title: AI Engineer
Role Summary: Design, develop, test, and deploy advanced AI and machine learning solutions using modern frameworks and cloud platforms, integrating them within enterprise service architectures and ensuring ethical compliance.
Expections: • Bachelor’s or Master’s degree in Computer Science, Engineering or related field; Master’s preferred • Minimum 9 years of professional IT experience with a focus on AI/ML • Fluency in English (written and spoken)
Key Responsibilities:
1. Develop and maintain AI applications (NLP, ML, generative models) that meet client business requirements.
2. Architect AI solutions, selecting appropriate models, techniques, and data pipelines for production.
3. Build, train, and optimise transformer‑based and other deep learning models on structured and unstructured data.
4. Implement data management practices, including metadata and model versioning, and integrate with SQL/NoSQL databases.
5. Deploy AI services on AWS or Azure, manage scaling, security, and monitoring.
6. Apply DevOps practices: Git, CI/CD, Docker, Kubernetes, and Agile workflows.
7. Present solution blueprints to technical and business stakeholders, facilitating feedback and alignment.
8. Champion best practices for MLOps, data governance, and ethical/legal considerations in AI deployments.
Required Skills:
• Python programming, core AI/ML/NLP libraries (pandas, sklearn, NLTK, spaCy, PyTorch, TensorFlow, OpenAI, Transformers, LangChain, CrewAI).
• Advanced AI techniques: large language models, generative AI, Retrieval-Augmented Generation, agentic workflows, function calling, multi‑turn prompts.
• Data engineering: pipelines, ETL, metadata management, SQL & NoSQL (Elasticsearch, MongoDB, Cassandra).
• Cloud platforms: AWS, Azure (deployment, scaling, security).
• DevOps/CI‑CD: Git, Docker, Kubernetes, automated pipelines, agile methodology.
• Strong documentation, testing, and integration of AI components into microservice architectures.
Required Education & Certifications: • Master’s degree in Computer Science, Information Technology, Data Science or related discipline (or equivalent experience). • Certifications in cloud (AWS Certified Solutions Architect, Azure AI Engineer Associate) and AI/ML frameworks are an asset.