Gen AI Solution Architect
The Gen AI Solution Architect provides technical leadership and designs complex solution architectures that support business strategy and streamline technology-enabled workflows. This position focuses on emerging technologies, including AI, Generative AI, and machine learning, and guides solutions from research and analysis through architecture, delivery support, and operational readiness.
Hands-on experience with GenAI and LLM solutions, including retrieval-augmented generation, embeddings, evaluation, and production monitoring.
• Experience with AI and ML platforms or services, such as AWS SageMaker, Amazon Bedrock, Azure AI, Azure OpenAI, or Google Vertex AI.
• Familiarity with MCP-based integrations and related agent tool standards, including skills and plugin manifests, function calling schemas, and OpenAPI-defined tools, plus secure enterprise integration patterns.
• Container and orchestration experience, such as Docker and Kubernetes, and cloud container platforms like ECS or EKS.
• Experience with vector databases and search technologies and associated indexing and retrieval patterns.
• Experience with enterprise observability, including centralized logging, tracing, metrics, alerting, and operational readiness.
• Database and procedural development experience, including PL/SQL, and strong data modeling concepts.
• Familiarity with responsible AI practices, governance controls, and security considerations specific to AI systems.
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Hands-on experience with GenAI and LLM solutions, including retrieval-augmented generation, embeddings, evaluation, and production monitoring.
• Experience with AI and ML platforms or services, such as AWS SageMaker, Amazon Bedrock, Azure AI, Azure OpenAI, or Google Vertex AI.
• Familiarity with MCP-based integrations and related agent tool standards, including skills and plugin manifests, function calling schemas, and OpenAPI-defined tools, plus secure enterprise integration patterns.
• Container and orchestration experience, such as Docker and Kubernetes, and cloud container platforms like ECS or EKS.
• Experience with vector databases and search technologies and associated indexing and retrieval patterns.
• Experience with enterprise observability, including centralized logging, tracing, metrics, alerting, and operational readiness.
• Database and procedural development experience, including PL/SQL, and strong data modeling concepts.
• Familiarity with responsible AI practices, governance controls, and security considerations specific to AI systems.
Apply Now
Apply Now