Provide architectural oversight across AI/ML projects to ensure consistency, performance, and maintainability
Evaluate and select AI technologies, frameworks, cloud services, vector databases, LLM orchestration frameworks, and tooling
Support development teams on model selection, training pipelines, prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), and evaluation methodologies
Mentor engineers, analysts, and product teams on AI best practices.

10+ years' experience enterprise-wide AI programs or platform buildouts
Strong understanding of data governance, privacy, security, and model risk management
Prior experience with large-scale transformation programs
Bachelor's degree in Computer Science, Engineering, or a related technical field
5+ years of experience in application development, engineering, or solution delivery roles
1+ years of hands-on experience in AI/ML engineering, data science, or AI solution architecture
Strong hands-on experience with machine learning frameworks and LLM platforms (e.g., OpenAI, Azure AI Foundry, Copilot Studio/Agent Builder, or comparable generative AI ecosystems)
Deep expertise in cloud platforms, particularly Microsoft Azure, and modern architectural patterns (microservices, event-driven architectures, API-first design)
Proficiency in one or more of the following: Python, Azure Machine Learning, or related AI/ML tooling
Experience with MLOps/LLMOps ecosystems, including tools such as MLflow, Kubernetes, LangChain, vector databases, and feature stores
Strong hands-on experience with ML frameworks, LLM platforms
OpenAI, MSFT/Azure Cloud foundry, Copilot Studio Agent builder, low code/no code platforms, and generative AI tools
Background in RAG systems, model fine-tuning, embeddings, vector storage, and retrieval optimization.

AI Architect

Key skills