• Consult on and enable successful execution of Data Science AI/ML and Generative AI solutions in assigned geo, focusing on Red Hat AI GTM. • Educate customers and stakeholders on the value of Red Hat's Data Science AI/ML and Generative AI offerings, highlighting their applications and benefits. • Lead and enable on hyper-competitive sales situations for the Data Science AI/ML and Generative AI portfolio, leveraging expertise in Predictive Analytics and Generative AI development practices. • Serve as a geo-level bi-directional conduit of GTM for Red Hat AI between sales, products, engineering, marketing, enablement, and customer success, ensuring seamless communication and collaboration. • Work closely with Red Hat AI product teams, providing feedback and identifying gaps in the offering to drive continuous improvement. • Build lasting relationships with cloud providers and other 3rd parties for joint GTM, focusing on Data Science AI/ML and Generative AI solutions. • Interface with regional sales leadership for account planning and GTM, ensuring alignment and effective execution of Red Hat AI sales strategies.

• Consult on and enable successful execution of Data Science AI/ML and Generative AI solutions in assigned geo, focusing on Red Hat AI GTM. • Educate customers and stakeholders on the value of Red Hat's Data Science AI/ML and Generative AI offerings, highlighting their applications and benefits. • Lead and enable on hyper-competitive sales situations for the Data Science AI/ML and Generative AI portfolio, leveraging expertise in Predictive Analytics and Generative AI development practices. • Serve as a geo-level bi-directional conduit of GTM for Red Hat AI between sales, products, engineering, marketing, enablement, and customer success, ensuring seamless communication and collaboration.

• Build agent architectures that are fast, reliable, and actually pleasant to work with • Research and ship techniques for agent reasoning, planning, and tool use • Create evaluation pipelines so we can measure whether agents are getting better or worse • Talk to users. Understand what's broken. Fix it.

• Own the text-to-SQL accuracy problem end-to-end: design evals, iterate prompts, and improve retrieval/routing • Build and operate the experimentation and evaluation loop (automatic evals, regression suites, dataset curation) • Design pragmatic LLM application architectures (RAG, agent routing, tool-use orchestration) optimized for accuracy and latency • Ship production-grade code and support deployments; instrument, monitor, and troubleshoot model behavior in real customer environments • Partner closely with engineering and customers to improve semantic models, SQL generation, and data alignment • Create feedback loops from users to systematically capture issues and convert them into measurable improvements • Contribute to automation of environment provisioning and dev workflows to enable fast iteration