AI Solution Architect

Job Description

The ideal candidate will be responsible for working cross-functionally to understand architecture needs by multiple business units. To be effective in this position, you must feel comfortable owning the entire architecture development process from inception to completion.

• Minimum 8 years in AI/ML roles, specialized in solutioning AI, ML and GenAI solutions.
• Proven experience in designing and deploying AI/ML and Generative AI solutions at scale across diverse business domains.
• Strong background in solutioning AI/ML and GenAI use cases, including translating business requirements into scalable technical architectures.
• Demonstrated expertise in solutioning Conversational AI systems, including intelligent chatbots and virtual assistants powered by LLMs.
• Deep understanding of machine learning, deep learning, and generative AI techniques, including model selection, training, and optimization.
• Hands-on experience in building and fine-tuning LLMs, including prompt engineering, Retrieval-Augmented Generation (RAG), and agentic workflows.
• Proficiency in developing robust ML pipelines using Azure ML or AWS SageMaker.
• Strong knowledge of cloud-native data storage and processing, including Azure Blob Storage, Tables, Queues, and Amazon S3.
• Experience deploying and operationalizing Azure Foundation Models and Azure OpenAI services in production environments.
• Skilled in containerization and DevOps practices, including Docker and CI/CD pipelines, for scalable and automated deployments.
• Advanced programming skills in Python, with a focus on clean, efficient, and maintainable code for AI/ML development.