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- Tasks: Lead the design and sales of generative AI and data modernization solutions.
- Company: Join Rackspace, a leader in innovative tech solutions.
- Benefits: Enjoy competitive salary, remote work options, and professional growth opportunities.
- Why this job: Make an impact by driving AI innovation and transforming data architectures.
- Qualifications: Deep experience in generative AI and data modernization required.
- Other info: Collaborate with C-level executives and shape the future of technology.
The predicted salary is between 72000 - 108000 £ per year.
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, 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). 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.
Responsibilities
- 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, 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 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, 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 (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, 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.
- 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, BigQuery).
- Guide architectural decisions on build vs. buy for both AI capabilities and data platform components.
Qualifications and required experience
- 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 senior-level architect or solutions leader with hands-on experience in both AI/ML and data platform modernization.
- Demonstrated success 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/Delta Lake, orchestration tools.
- Proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences.
Preferred Qualifications
- 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.
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.
Educational Requirements
- Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or related technical field.
- Advanced degree (Master's or PhD) in a relevant field is highly preferred.
Solutions Director - Analytics & AI employer: Rackspace Technology
Contact Detail:
Rackspace Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Solutions Director - Analytics & AI
✨Tip Number 1
Network like a pro! Get out there and connect with industry folks on LinkedIn or at events. The more people you know, the better your chances of landing that Solutions Director gig.
✨Tip Number 2
Show off your skills! Prepare a killer presentation or demo showcasing your expertise in generative AI and data modernization. This is your chance to impress potential employers with what you can bring to the table.
✨Tip Number 3
Don’t just apply; engage! When you find a role that excites you, reach out directly to the hiring manager or team. A personal touch can make all the difference and show your genuine interest in the position.
✨Tip Number 4
Stay updated! Keep an eye on the latest trends in AI and data platforms. Being knowledgeable about current advancements will help you stand out in interviews and discussions with C-level stakeholders.
We think you need these skills to ace Solutions Director - Analytics & AI
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Solutions Director role. Highlight your experience with generative AI and data modernization, and show us how you can drive top-of-funnel opportunities.
Showcase Your Expertise: We want to see your mastery of both generative AI and data platforms. Include specific examples of projects you've led or contributed to, especially those involving AWS services like Glue and SageMaker.
Engage with Our Values: Familiarise yourself with our company culture and values. In your application, reflect how your personal values align with ours, particularly in terms of innovation and customer engagement.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensure you’re considered for this exciting opportunity.
How to prepare for a job interview at Rackspace Technology
✨Know Your Tech Inside Out
Make sure you’re well-versed in the specific technologies mentioned in the job description, like Amazon Bedrock, QuickSight, and lakehouse architectures. Brush up on your knowledge of generative AI and data platforms, as you’ll likely be asked to discuss how these can drive business value.
✨Engage with C-Level Conversations
Prepare to demonstrate your ability to engage with C-level stakeholders. Think about how you can present complex technical concepts in a way that highlights their business impact. Practise articulating your vision for generative AI and data modernization in a compelling manner.
✨Showcase Your Strategic Thinking
Be ready to discuss how you would approach opportunity creation and solution design. Prepare examples from your past experiences where you’ve successfully led similar initiatives, especially those involving generative AI or data platform transformations.
✨Ask Insightful Questions
During the interview, don’t hesitate to ask questions that show your interest in the company’s strategy and challenges. Inquire about their current projects in generative AI and data modernization, and how they envision the role contributing to their goals. This will demonstrate your proactive mindset and strategic thinking.
