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

• 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: • o   Generative AI Solutions: Amazon Bedrock implementations, Amazon Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions • o   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: • o   Executive Level: Amazon Q demonstrations, QuickSight analytics with generative BI, art-of-the-possible sessions • o   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

🎯 Requirements

• Dual Expertise Required: • o   Deep experience with generative AI technologies: Amazon Bedrock, Amazon Q, LLM architectures, RAG implementations • o   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: • o   AI/ML: Generative AI, foundation models, LLMs, traditional ML, prompt engineering, fine-tuning • o   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

🏖️ Benefits

• Opportunity to lead dual portfolios at the intersection of generative AI innovation and data platform modernization • Direct engagement with C-level executives on transformational initiatives • Access to latest AWS technologies across AI and data services • Work with leading platforms: Databricks, Snowflake, AWS native services • Comprehensive professional development and certification support • Competitive compensation and benefits package