Solutions Director - Analytics & AI

Rackspace is seeking a highly accomplished Solution Director, Analytics & AI to lead the design and sales of two critical solution portfolios: generative AI/LLM solutions and data modernization/lakehouse architectures on AWS. This pivotal role requires mastery of both domains - leveraging generative AI capabilities (Amazon Q, Amazon Bedrock, Quick Sight) to drive executive conversations and opportunity creation, while delivering enterprise data modernization through lakehouse architectures using AWS native services (Glue, Sage Maker Unified Studio) and leading platforms (Databricks on AWS, Snowflake on AWS).

The position demands cross-functional experience with proven ability to engage C-level stakeholders, drive top-of-funnel opportunity creation, and maintain comprehensive account ownership across the entire customer lifecycle.

• Strategic Leadership & Opportunity Development
• Drive top-of-funnel opportunity creation through two parallel tracks: engaging C-level stakeholders with generative AI demonstrations (Amazon Q, Amazon Bedrock) and identifying data modernization needs for lakehouse transformations
• Lead the design and architecture of dual solution portfolios:
• - Generative AI Solutions, Amazon Bedrock implementations, Amazon Q deployments, Quick Sight with Q capabilities, RAG architectures, and custom LLM solutions
• - Data Modernization:
  Enterprise lakehouse architectures using AWS Glue, Sage Maker Unified Studio, Databricks on AWS, and Snowflake on AWS
• Act as the trusted advisor positioning generative AI as the transformational vision while grounding delivery in robust data platform modernization
• Develop compelling business cases that connect AI aspirations with practical data foundation requirements, demonstrating ROI across both portfolios
• Stay current with advancements in generative AI (foundation models, LLMs) and modern data architectures (lakehouse patterns, data mesh, unified analytics)
• Contribute to Rackspace intellectual property through reference architectures covering both generative AI implementations and lakehouse design patterns
• Customer Engagement & Solution Delivery
• Serve as the primary technical executive orchestrating both generative AI discussions and data modernization programs for strategic accounts
• Build strategic relationships using two engagement models:
• - Executive Level: Amazon Q demonstrations, Quick Sight analytics with generative BI, art-of-the-possible sessions
• - Technical Level: Lakehouse architecture workshops, platform assessments (Databricks vs Snowflake vs AWS-native), migration planning
• Lead comprehensive consultative engagements that begin with generative AI vision (Amazon Q, Bedrock) and translate into concrete data modernization roadmaps
• Develop Statements of Work (SOWs) that balance innovative AI capabilities with foundational data platform requirements
• Guide customers through parallel journeys: generative AI adoption (POCs to production) and data platform modernization (legacy to lakehouse)
• Collaborate with sales teams positioning both solution portfolios strategically based on customer maturity and needs
• Technical Excellence & Market Awareness
• Maintain deep expertise across both solution domains:
• - Generative AI:
  Amazon Bedrock, Amazon Q, Quick Sight Q, Sage Maker Jump Start, prompt engineering, RAG architectures, vector databases
• - Data Platforms: AWS Glue, Sage Maker Unified Studio, Databricks on AWS, Snowflake on AWS, Redshift, EMR, Apache Iceberg, Delta Lake
• Demonstrate comprehensive understanding of how generative AI solutions depend on modern data foundations
• Position AWS solutions effectively against other cloud platforms' offerings in both generative AI (Azure OpenAI, Vertex AI) and data platforms (Azure Synapse, Big Query)
• Guide architectural decisions on build vs. buy for both AI capabilities and data platform components

• Deep experience with generative AI technologies:
  Amazon Bedrock, Amazon Q, LLM architectures, RAG implementations
• Proven track record delivering data modernization: lakehouse architectures, Databricks and/or Snowflake implementations, AWS Glue/EMR deployments
• At least 5 years as a…