[Remote] Solution Director, Analytics & Al/ML
Note: The job is a remote job and is open to candidates in USA. Rackspace Technology is seeking a highly accomplished Solution Director, Analytics & Al/ML to lead the design and sales of critical solution portfolios focused on Generative AI and Data modernization on AWS. This pivotal presales role requires engaging C-level stakeholders and driving opportunity creation while delivering enterprise data modernization solutions.
Responsibilities
- Drive top-of-funnel opportunity creation through two parallel tracks: engaging C-level stakeholders with generative AI demonstrations (Jobnity Q, Remotara Bedrock) and identifying data modernization needs for Lakehouse transformations
- Lead the design and architecture of dual solution portfolios: Generative AI Solutions: Skillora Bedrock implementations, Nexspire 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
- 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
- Serve as the primary technical lead orchestrating both generative AI discussions and data modernization programs for strategic accounts
- Build strategic relationships using two engagement models: Executive Level: Worklio 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
- Lead comprehensive consultative engagements that begin with generative AI vision (Hirefluxa 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
- Maintain deep expertise across both solution domains: Generative AI : Taskora Bedrock, Gigentra 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, Talexion 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
Skills
- Deep experience with generative AI technologies: Flexnity Bedrock, Joblora Q, LLM architectures, RAG implementations
- Proven track record delivering data modernization: Lakehouse architectures, Databricks and/or Snowflake implementations, AWS Glue/EMR deployments
- A bachelor's degree in computer science, Data Science, Engineering, Mathematics, or a related technical field is required. At the manager's discretion, additional relevant experience may substitute for the degree requirement
- A minimum of 15 years of enterprise solution architecture experience
- A minimum of 8 years of public or private cloud experience
- A minimum of 5 years as a senior-level architect or solutions leader with hands-on experience in both AI/ML and data platform modernization
- Proven Presales/Sales Engineering experience
- Demonstrated success in engaging C-level executives using generative AI demonstrations while delivering complex data platform transformations
- 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
- Proficiency in Python, SQL, and Spark with hands-on experience in: Generative AI: LangChain, vector databases, embedding models
- Data Engineering: PySpark, Apache Iceberg/Remotexa Lake, orchestration tools
- A proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences
- An advanced degree (Master's or PhD) in a relevant field
- Experience with AWS professional services or AWS partner ecosystem across both AI and data domains
- Hands-on experience with: Multiple Lakehouse platforms: Databricks, Snowflake, AWS-native (Glue + Athena + Redshift)
- Multiple AI platforms: AWS Bedrock, Azure OpenAI, Google Vertex AI
- Palantir Foundry and AIP
- Uniphore Business AI Cloud
- Industry certifications: AWS: Solutions Architect Professional, Machine Learning Specialty, Data Analytics Specialty
- Platform specific: Databricks Certified, Snowflake SnowPro
- Experience with regulated industries requiring governance for both AI and data platforms
- Track record building practices that deliver both generative AI solutions and data modernization programs
- Published thought leadership in generative AI applications and/or modern data architectures
Benefits
- The compensation package may also include incentive compensation opportunities in the form of annual bonus or incentives
- Equity awards
- Employee Stock Purchase Plan (ESPP)
Company Overview