AI & Data Solutions Architect
RemoteSeattle, Washington, United States
Job Summary
Lead enterprise engagements by acting as the primary technical strategist during presales cycles, partnering with Sales to define solution scope and build narratives for C-suite stakeholders. Architect scalable, cloud-native software solutions and modern data platforms aligned with AI initiatives, while providing hands-on execution through script development, proof-of-concept building, and technical escalations to global delivery teams. Design advanced AI/ML solutions including Agentic AI workflows and secure integrations, ensuring adherence to governance frameworks and optimizing cloud architectures across Azure, AWS, and GCP. Translate complex technical concepts into business value for executive presentations and guide internal R&D efforts on product accelerators.
Required Qualifications
- 8+ years in client-facing presales, consulting, or solution architecture roles
- Exceptional white boarding and communication skills
- Demonstrated capability to dynamically design and articulate modern data architectures for both engineering leadership and business executives
- Experience mentoring development teams and partnering seamlessly across a global delivery model
- 7+ years designing cloud-native architectures (Azure, AWS, or GCP)
- Deep architectural knowledge of modern data platforms (preferably Databricks or Microsoft Fabric)
- Experience with distributed compute frameworks (Apache Spark)
- Strong architectural experience designing AI/ML solutions, vector databases, and RAG architectures
- Expertise in developing Agentic AI systems and workflow automation utilizing frameworks such as LangChain and the Model Context Protocol (MCP)
- Retained hands-on engineering proficiency with a strong command of Python and SQL
- Experience in highly scalable backend languages like Java or Go
- Fully capable of executing detailed technical work and navigating the modern SDLC
- Active utilization of AI productivity tools (e.g., GitHub Copilot, Claude) to accelerate development
- Solid understanding of containerization (Docker, Kubernetes) and CI/CD pipelines
- Expertise in designing robust data pipelines, semantic models, and API integrations that seamlessly connect AI capabilities within complex, legacy enterprise environments (e.g., SAP, Oracle)
Desired Qualifications
- Experience with Microsoft Fabric
- Experience with Databricks
- Experience with Apache Spark
- Experience with LangChain
- Experience with the Model Context Protocol (MCP)
- Experience with Java
- Experience with Go
- Experience with Docker
- Experience with Kubernetes
- Experience with CI/CD pipelines
- Experience with SAP
- Experience with Oracle
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