Senior AI/ML Architect, Applied Field Engineering

Role overview This senior applied AI and machine learning role helps technical customer teams design, build, and validate cloud based solutions for enterprise use cases. You’ll combine hands-on architecture guidance with field engineering, working across customer, sales, product, and engineering teams to support successful proofs of concept and adoption.

Responsibilities - Explain AI and machine learning capabilities to technical decision makers and data scientists, connecting solution design to customer needs. - Scope and guide proofs of concept with account teams and customer champions, then present results and business value to technical and executive audiences. - Bring customer feedback to product and engineering teams to help shape AI and machine learning roadmaps. - Create reusable technical materials, such as demonstrations, notebooks, presentations, conference content, and customer stories. - Maintain and tailor technical sales assets for AI and machine learning solutions.

Requirements - At least five years of experience building and deploying machine learning and generative AI solutions in cloud environments. - Working knowledge of generative AI methods, including retrieval augmented generation, few shot learning, prompt engineering, or fine tuning, and how they support enterprise applications such as chat and text processing. - Strong Python skills and familiarity with machine learning libraries such as pandas, scikit learn, PyTorch, or LangChain. - Experience with data engineering technologies such as dbt, Airflow, or Spark. - Confident presenting and explaining technical ideas through whiteboarding, demonstrations, and formal readouts. - Bachelor’s degree required; a relevant master’s degree or equivalent experience is preferred.

Nice to have - Familiarity with LLM ecosystem tools such as LangChain, LlamaIndex, or other open source packages. - Experience with major cloud infrastructure platforms and large scale database technologies. - At least one year of practical experience with a cloud data platform.