Rackspace
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 & Al/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: 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'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. Customer Engagement & Solution Delivery • 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: 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 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. Technical Excellence & Market Awareness Maintain deep expertise across both solution domains: 1) Generative AI: Amazon Bedrock, Amazon Q, QuickSight Q, SageMaker JumpStart, prompt engineering, RAG architectures, vector databases. 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. 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. 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. 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/Delta Lake, orchestration tools. A proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences. Preferred Qualifications 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. 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.
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 & Al/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: 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'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. Customer Engagement & Solution Delivery • 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: 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 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. Technical Excellence & Market Awareness Maintain deep expertise across both solution domains: 1) Generative AI: Amazon Bedrock, Amazon Q, QuickSight Q, SageMaker JumpStart, prompt engineering, RAG architectures, vector databases. 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. 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. 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. 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/Delta Lake, orchestration tools. A proven ability to articulate both visionary AI possibilities and practical data platform requirements to diverse audiences. Preferred Qualifications 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. 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.
Harrington Starr
AWSContactCentre/AmazonConnect-SoftwareEngineer Contract 12months Hybrid(UK?based) Upto£700perdayInsideIR35 We're partnering with a major UK enterprise expanding its AWS Contact Centre engineering capability. The team is building new features and services across multiple AmazonConnect instances and needs hands?onSeniorSoftwareEngineers who can design, build and support scalable, production?gradesolutions. This role is fully engineering? focused-notanarchitectposition. You'll be coding daily, working with AmazonConnect, Lex, Lambdas and modern TypeScript/Python across serverless architectures. If you're a hands?on engineer with strong AmazonConnect/Lex experience and want to build real, high?impact products in a large?scale environment, we'd love to hear from you. The role You will work with cross?functional product and engineering teams to: Design, develop and enhance services using AmazonConnect, AmazonLex, ContactFlows, Lambda, and LLM?driven capabilities Build new features and maintain existing products across multiple Connect environments Write clean, maintainable code in TypeScript, JavaScript, and Python Implement DevOps best practices: CI/CD, automated testing, monitoring, infrastructure?as?code Participate in code reviews and uphold strong engineering standards Troubleshoot complex issues across AWS services, contact flows and application layers Stay current with emerging AWS and AI technologies to support continuous improvement Key Requirements Proven experience as SeniorSoftwareEngineer Hands?on AWS engineering, especially: AmazonConnect ContactFlows/IVR AmazonLex Lambda(Node/Python) Strong coding ability in TypeScript, modern JavaScript frameworks and Python Experience integrating contactcentre technologies into enterprise systems Solid grounding in serverless, CI/CD, monitoring, and cloud?native engineering Excellent problem?solving skills and communication Nice to have Experience with LLMs or AWS AI/ML services Knowledge of microservices and secure cloud engineering Experienced delivering within Agile teams Contract Details 12?monthcontract Hybrid-3 days in London Upto£700/day If you're a hands?on engineer with strong AmazonConnect/Lex experience and want to build real, high?impact products in a large?scale environment, we'd love to hear from you. Apply now ?
AWSContactCentre/AmazonConnect-SoftwareEngineer Contract 12months Hybrid(UK?based) Upto£700perdayInsideIR35 We're partnering with a major UK enterprise expanding its AWS Contact Centre engineering capability. The team is building new features and services across multiple AmazonConnect instances and needs hands?onSeniorSoftwareEngineers who can design, build and support scalable, production?gradesolutions. This role is fully engineering? focused-notanarchitectposition. You'll be coding daily, working with AmazonConnect, Lex, Lambdas and modern TypeScript/Python across serverless architectures. If you're a hands?on engineer with strong AmazonConnect/Lex experience and want to build real, high?impact products in a large?scale environment, we'd love to hear from you. The role You will work with cross?functional product and engineering teams to: Design, develop and enhance services using AmazonConnect, AmazonLex, ContactFlows, Lambda, and LLM?driven capabilities Build new features and maintain existing products across multiple Connect environments Write clean, maintainable code in TypeScript, JavaScript, and Python Implement DevOps best practices: CI/CD, automated testing, monitoring, infrastructure?as?code Participate in code reviews and uphold strong engineering standards Troubleshoot complex issues across AWS services, contact flows and application layers Stay current with emerging AWS and AI technologies to support continuous improvement Key Requirements Proven experience as SeniorSoftwareEngineer Hands?on AWS engineering, especially: AmazonConnect ContactFlows/IVR AmazonLex Lambda(Node/Python) Strong coding ability in TypeScript, modern JavaScript frameworks and Python Experience integrating contactcentre technologies into enterprise systems Solid grounding in serverless, CI/CD, monitoring, and cloud?native engineering Excellent problem?solving skills and communication Nice to have Experience with LLMs or AWS AI/ML services Knowledge of microservices and secure cloud engineering Experienced delivering within Agile teams Contract Details 12?monthcontract Hybrid-3 days in London Upto£700/day If you're a hands?on engineer with strong AmazonConnect/Lex experience and want to build real, high?impact products in a large?scale environment, we'd love to hear from you. Apply now ?
