Solution Director, Analytics & AI/ML

Role Overview

• 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.
• 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.

Requirements

• Dual Expertise Required:
• 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.
• 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.

Tech Stack

• Apache
• AWS
• Cloud
• ETL
• PySpark
• Python
• Spark
• SQL

Benefits

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