Responsibilities

• Design, build, and deploy end-to-end AI solutions — from model selection and prototyping to production-grade pipelines — on cloud platforms such as Azure, GCP (Vertex AI), or Databricks.
• Co-facilitate AI discovery workshops and ideation sessions with client teams, translating business challenges into actionable AI use cases and architecture recommendations.
• Advise clients on AI architecture decisions, model selection, MLOps best practices, and platform choices, adapting recommendations to their technical maturity and constraints.
• Develop and integrate GenAI solutions including RAG architectures, LLM-based agents, prompt engineering, and agentic workflows using tools such as LangChain, Azure AI Foundry, or Databricks Model Serving.
• Contribute to AI strategy and governance engagements by supporting use case scoring, roadmap design, and the definition of AI governance foundations alongside the AI Lead.
• Build...