Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
8+ years of experience in ML engineering, data science, or software architecture, with 3+ years in AI/ML solution design
Proficiency in Python, R, or Julia for AI/ML development
Expertise in ML frameworks like TensorFlow, PyTorch, Hugging Face, or Scikit-learn
Experience with cloud platforms (AWS, Azure, Google Cloud) and AI services like Amazon Bedrock or Azure AI Foundry
Knowledge of MLOps tools (e.g., Kubeflow, MLflow) and CI/CD pipelines
Familiarity with generative AI techniques, including prompt engineering, fine-tuning, and RAG
Understanding of data engineering concepts, including ETL processes and data lakes
Strong communication to bridge technical and business teams
Analytical thinking for evaluating trade-offs and designing optimal solutions
Leadership and mentorship to guide cross-functional teams
Experience in industries like healthcare, finance, or technology, with an understanding of relevant use cases (e.g., drug discovery, personalized marketing)
Certifications AWS Certified Machine Learning – Specialty, Microsoft Azure AI Engineer Associate, Google Cloud Professional Machine Learning Engineer, Coursera or Edureka AI/ML certifications (e.g., DeepLearning.AI’s Generative AI Specialization), ITIL or TOGAF for enterprise architecture alignment (optional).

AI Solution Architect

Key skills