Core Technical Requirements
Programming Proficiency:
Strong experience with Python, plus one or more languages such as Java, JavaScript etc.
AI/ML Expertise:
Hands-on experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, etc.)
Understanding of deep learning architectures (CNNs, RNNs, Transformers, etc.)
Familiarity with LLMs, prompt engineering, and fine-tuning techniques.
Strong knowledge of data preprocessing, feature engineering, and model evaluation.
Cloud & Infrastructure:
Experience deploying AI/ML models on cloud platforms (Azure).
Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.
Strong understanding of version control (Git), code reviews, and testing.
Experience building scalable APIs and microservices for AI applications
Excellent written and verbal communication skills - able to translate complex AI concepts for technical and non-technical audiences. Proven ability to work cross-functionally with product managers, data scientists, and business stakeholders. Comfortable leading technical discussions, demos, and documentation.
Educational & Experience Requirements
Bachelor's or master's degree in computer science, Engineering, Mathematics, or related field. 2 5 years of hands-on AI/ML development experience.
Preferred / Bonus Skills
Experience with Generative AI (OpenAI, Anthropic, Hugging Face, etc.)
Familiarity with LLM orchestration frameworks (LangChain, Semantic Kernel).
Knowledge of responsible AI, model explainability, and bias mitigation.
Contribution to open-source AI projects or research publications. (For AI Architect)
Experience mentoring junior engineers. (For AI Architect)
Key Soft Skills
Problem-solving mindset with creativity and adaptability.
Ownership and accountability for deliverables.
Continuous learner - stays current with evolving AI technologies.
Team player with collaborative and inclusive communication style.