Job Specifications
Rackspace Technology is a leading provider of expertise and managed services across all the major public and private cloud technologies. We’ve evolved Fanatical Support to encompass the entire customer journey — providing Fanatical Experience™ from first consultation to daily operations. Our passionate experts combine the power of proactive, always-on service and expertise with best-in-class tools and automation to deliver technology when and how our customers need it.
We are seeking a highly accomplished Solution Director (Analytics & Al/ML) 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, QuickSight) to drive executive conversations and opportunity creation, while delivering enterprise data modernization through Lakehouse architectures using AWS native services (Glue, SageMaker Unified Studio) and leading platforms (Databricks on AWS, Snowflake on AWS).
This is a presales role that 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.
The ideal candidate will excel at both selling the vision of generative AI transformation and delivering the reality of enterprise data modernization, combining deep technical expertise with exceptional business acumen and executive presence.
Responsibilities
Strategic Leadership & Opportunity Development
Lead the design and architecture of dual solution portfolios:
Generative AI Solutions: Amazon Bedrock implementations, Amazon Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions
Data Modernization: Enterprise Lakehouse architectures using AWS Glue, SageMaker Unified Studio, Databricks on AWS, and Snowflake on AWS
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
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's intellectual property through reference architectures covering both generative AI implementations and Lakehouse design patterns
Mentor and provide leadership to Solution Architects by guiding technical development and fostering skill growth across both generative AI and data modernization solution areas
Customer Engagement & Solution Delivery
Build strategic relationships using two engagement models:
Executive Level: Amazon Q demonstrations, QuickSight analytics with generative BI, art-of-the-possible sessions
Technical Level: Lakehouse architecture workshops, platform assessments (Databricks vs Snowflake vs AWS-native), migration planning
Serve as the primary technical lead orchestrating both generative AI discussions and data modernization programs for strategic accounts
Lead comprehensive consultative engagements that begin with generative AI vision (Amazon Q, Bedrock) and translate into concrete data modernization roadmaps
Develop proposals 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 to position 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, QuickSight Q, SageMaker JumpStart, prompt engineering, RAG architectures, vector databases
Data Platforms: AWS Glue, SageMaker Unified Studio, Databricks on AWS, Snowflake on AWS, Redshift, EMR, Apache Iceberg, Delta Lake
Position AWS solutions effectively against other cloud platforms' offerings in both generative AI (Azure OpenAI, Vertex AI) and data platforms (Azure Synapse, BigQuery)
Guide architectural decisions on build vs. buy for both Al capabilities and data platform components
Required Experience
Strong understanding across the full spectrum:
AI/ML: Generative AI, foundation models, LLMs, traditional ML, prompt engineering, fine-tuning
Data Platforms: Lakehouse architectures, data mesh, ETL/ELT, streaming, data governance, data quality
Deep experience with generative AI technologies: Amazon Bedrock, Amazon Q, LLM architecture