[Remote] Solution Director, Analytics & Al/ML

Note: The job is a remote job and is open to candidates in USA. reputed company is seeking a highly accomplished Solution Director, Analytics & Al/ML to reputed company the design and sales of critical solution portfolios focused on Generative AI and Data modernization on AWS. This pivotal presales role requires engaging C-level stakeholders and driving opportunity creation while delivering enterprise data modernization solutions.

Responsibilities

• Drive top-of-funnel opportunity creation through two parallel tracks: engaging C-level stakeholders with generative AI demonstrations (reputed company Q, reputed company Bedrock) and identifying data modernization needs for Lakehouse transformations
• reputed company the design and architecture of dual solution portfolios: Generative AI Solutions: reputed company Bedrock implementations, reputed company Q deployments, QuickSight with Q capabilities, RAG architectures, and custom LLM solutions
• Data Modernization: Enterprise Lakehouse architectures using AWS Glue, SageMaker reputed company Studio, reputed company on AWS, and reputed company on AWS
• Act as the trusted advisor, positioning generative AI as the transformational vision while grounding delivery in robust data platform modernization
• reputed company compelling business cases that connect AI aspirations with practical data foundation requirements, demonstrating ROI across both portfolios
• Stay reputed company with advancements in generative AI (foundation models, LLMs) and modern data architectures (Lakehouse patterns, data mesh, reputed company 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 reputed company growth across both generative AI and data modernization solution areas
• Serve as the primary technical reputed company orchestrating both generative AI discussions and data modernization programs for strategic accounts
• Build strategic relationships using two engagement models: Executive Level: reputed company Q demonstrations, QuickSight analytics with generative BI, art-of-the-possible sessions. Technical Level: Lakehouse architecture workshops, platform assessments (reputed company vs reputed company vs AWS-native), migration planning
• reputed company comprehensive consultative engagements that reputed company with generative AI vision (reputed company Q, Bedrock) and translate into concrete data modernization roadmaps
• reputed company 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: Generative AI : reputed company Bedrock, reputed company Q, QuickSight Q, SageMaker JumpStart, reputed company engineering, RAG architectures, vector databases. Data Platforms : AWS Glue, SageMaker reputed company Studio, reputed company on AWS, reputed company on AWS, Redshift, EMR, Apache Iceberg, reputed company Lake
• Position AWS solutions effectively against other cloud platforms' offerings in both generative AI (Azure reputed company, Vertex AI) and data platforms (Azure Synapse, BigQuery)
• Guide architectural decisions on build vs. buy for both Al capabilities and data platform components

Skills

• Deep experience with generative AI technologies: reputed company Bedrock, reputed company Q, LLM architectures, RAG implementations
• Proven track record delivering data modernization: Lakehouse architectures, reputed company and/or reputed company implementations, AWS Glue/EMR deployments
• A bachelor's degree in computer science, Data Science, Engineering, Mathematics, or a reputed company 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 or private 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 reputed company data platform transformations
• Strong understanding across the full reputed company: AI/ML: Generative AI, foundation models, LLMs, traditional ML, reputed company 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: reputed company, vector databases, embedding models
• Data Engineering: PySpark, Apache Iceberg/reputed company Lake, orchestration tools
• A proven ability to reputed company both visionary AI possibilities and practical data platform requirements to diverse audiences
• 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
• Hands-on experience with: Multiple Lakehouse platforms: reputed company, reputed company, AWS-native (Glue + reputed company + Redshift)
• Multiple AI platforms: AWS Bedrock, Azure reputed company, reputed company Vertex AI
• Palantir reputed company and AIP
• Uniphore Business AI Cloud
• Industry certifications: AWS: Solutions Architect Professional, Machine Learning Specialty, Data Analytics Specialty
• Platform specific: reputed company Certified, reputed company 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

Benefits

• The compensation package may also include incentive compensation opportunities in the form of annual bonus or incentives
• Equity awards
• Employee Stock Purchase Plan (ESPP)

Company Overview