Solutions Director – Analytics & AI

November 26

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Rackspace Technology

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SaaS • Cloud

Rackspace Technology is a leading provider of managed cloud services, offering a comprehensive range of cloud and application solutions. The company specializes in helping businesses increase efficiency and reliability through cloud adoption, application modernization, and data solutions, leveraging technologies such as AI, machine learning, and next-gen data platforms. They offer a full suite of services including consulting, application modernization, cloud security, and multicloud strategies, tailoring solutions to meet the specific needs of sectors such as healthcare, financial services, and public utilities. Rackspace Technology is known for its expertise in navigating complex cloud environments and providing advanced managed services to optimize performance and ensure compliance.

5001 - 10000 employees

Founded 1998

☁️ SaaS

📋 Description

• 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 • 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 and Technical Level • Lead comprehensive consultative engagements that begin with generative AI vision and translate into concrete data modernization roadmaps • Develop Statements of Work (SOWs) that balance innovative AI capabilities with foundational data platform requirements • Collaborate with sales teams positioning both solution portfolios strategically based on customer maturity and needs

🎯 Requirements

• 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

🏖️ Benefits

• Competitive salary • Professional development opportunities