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- Tasks: Lead the design and sales of innovative AI and data solutions.
- Company: Join Rackspace Technology, a leader in cloud services and support.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Shape the future of AI and data modernization while engaging with top executives.
- Qualifications: 15+ years in enterprise architecture with expertise in AI/ML and data platforms.
- Other info: Dynamic role with mentorship opportunities and strategic impact on customer journeys.
The predicted salary is between 100000 - 130000 £ per year.
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 & AI/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: 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; 1) Generative AI Solutions: Amazon Bedrock implementations, Amazon Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions, and 2) 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; 1) Executive Level: Amazon Q demonstrations, QuickSight analytics with generative BI, art-of-the-possible sessions, and 2) 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 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; 1) Generative AI: Amazon Bedrock, Amazon Q, QuickSight Q, SageMaker JumpStart, prompt engineering, RAG architectures, vector databases, and 2) 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 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.
- 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 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.
- 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.
- Proficiency in Python, SQL, and Spark with hands-on experience in: Data Engineering: PySpark, Apache Iceberg/Delta Lake, orchestration tools.
- A proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences.
Solution Director; Analytics, AI/ML (Presales) in London employer: Rackspace Technology
Contact Detail:
Rackspace Technology Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Solution Director; Analytics, AI/ML (Presales) in London
✨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 dream job. Plus, personal referrals can really make your application stand out.
✨Tip Number 2
Show off your skills in real-time! If you get the chance, ask for a demo or presentation opportunity during interviews. This is your moment to shine and demonstrate your expertise in generative AI and data modernization directly to potential employers.
✨Tip Number 3
Research the company inside out! Understand their products, culture, and recent news. This will help you tailor your conversations and show that you're genuinely interested in what they do, especially in areas like AWS solutions and AI technologies.
✨Tip Number 4
Don’t forget to follow up! After interviews or networking chats, send a quick thank-you note. It keeps you fresh in their minds and shows your enthusiasm for the role. And remember, apply through our website for the best chance!
We think you need these skills to ace Solution Director; Analytics, AI/ML (Presales) in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Solution Director role. Highlight your experience with generative AI and data modernization, and show us how your skills align with what we're looking for.
Showcase Your Expertise: We want to see your deep knowledge in both generative AI and data platforms. Include specific examples of projects you've worked on, especially those involving AWS services like Glue or SageMaker, to demonstrate your technical prowess.
Engage with Our Values: At StudySmarter, we value a proactive approach. In your application, reflect on how you’ve driven top-of-funnel opportunities and engaged C-level stakeholders in previous roles. This will help us see your fit within our culture.
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 ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at Rackspace Technology
✨Know Your Tech Inside Out
Make sure you’re well-versed in the 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 need to demonstrate your expertise during the interview.
✨Engage with C-Level Scenarios
Prepare to discuss how you would engage C-level stakeholders. Think about specific examples where you've successfully led discussions or demonstrations that highlight the value of generative AI and data modernization. This will show your ability to drive top-of-funnel opportunities.
✨Craft Compelling Business Cases
Be ready to articulate how you would develop business cases that connect AI aspirations with practical data foundation requirements. Think of examples from your past experience where you demonstrated ROI through innovative solutions, as this is crucial for the role.
✨Showcase Your Leadership Skills
Since mentoring and guiding Solution Architects is part of the role, prepare to discuss your leadership style and experiences. Share instances where you’ve fostered skill growth in others, particularly in the realms of AI/ML and data modernization.