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 and Data Modernization.
Develop compelling business cases connecting AI aspirations with practical data foundation requirements, demonstrating ROI across both portfolios.
Stay current with advancements in generative AI and modern data architectures.
Serve as the primary technical lead orchestrating both generative AI discussions and data modernization programs for strategic accounts.
Build strategic relationships using executive and technical level engagement models.

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 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 complex data platform transformations.
Strong understanding across the full spectrum: AI/ML: Generative AI, foundation models, LLMs, traditional ML, prompt engineering, fine-tuning.
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.

Solution Director, Analytics & AI/ML

Key skills