Key Responsibilities

What you will be responsible for

• Design end-to-end solution architectures that integrate AWS cloud services, enterprise data platforms, application services, AI capabilities, cybersecurity controls, and operational workflows.
• Translate business, technology, cyber, and data requirements into practical architecture patterns, reference designs, technical roadmaps, and implementation guidance.
• Develop solution approaches for GenAI and LLM-enabled products, including RAG patterns, prompt and context strategies, knowledge retrieval, agentic workflows, AI orchestration, and human-in-the-loop operating models.
• Partner with data engineering and analytics teams to design scalable data ingestion, transformation, governance, metadata, lineage, and consumption patterns that support AI and enterprise analytics use cases.
• Collaborate with cybersecurity, risk, and control teams to embed secure-by-design principles, identity and access controls, logging, monitoring, data protection, and responsible AI considerations into solution designs.
• Create architecture artifacts such as conceptual diagrams, logical designs, integration patterns, data flows, sequence views, decision records, and executive-ready solution summaries.
• Evaluate technology options, identify trade-offs, and recommend architecture choices that balance scalability, cost, resiliency, security, maintainability, adoption, and time-to-value.
• Support delivery teams through design reviews, technical problem solving, proof-of-concept development, implementation planning, and transition from architecture into engineering execution.
• Contribute to enterprise standards, reusable patterns, architecture guardrails, and governance practices for cloud, data, and AI-enabled solutions.

Key Responsibilities

What you will be responsible for

• Design end-to-end solution architectures that integrate AWS cloud services, enterprise data platforms, application services, AI capabilities, cybersecurity controls, and operational workflows.
• Translate business, technology, cyber, and data requirements into practical architecture patterns, reference designs, technical roadmaps, and implementation guidance.
• Develop solution approaches for GenAI and LLM-enabled products, including RAG patterns, prompt and context strategies, knowledge retrieval, agentic workflows, AI orchestration, and human-in-the-loop operating models.
• Partner with data engineering and analytics teams to design scalable data ingestion, transformation, governance, metadata, lineage, and consumption patterns that support AI and enterprise analytics use cases.
• Collaborate with cybersecurity, risk, and control teams to embed secure-by-design principles, identity and access controls, logging, monitoring, data protection, and responsible AI considerations into solution designs.
• Create architecture artifacts such as conceptual diagrams, logical designs, integration patterns, data flows, sequence views, decision records, and executive-ready solution summaries.
• Evaluate technology options, identify trade-offs, and recommend architecture choices that balance scalability, cost, resiliency, security, maintainability, adoption, and time-to-value.
• Support delivery teams through design reviews, technical problem solving, proof-of-concept development, implementation planning, and transition from architecture into engineering execution.
• Contribute to enterprise standards, reusable patterns, architecture guardrails, and governance practices for cloud, data, and AI-enabled solutions.