Specialist Solutions Architect - AI/MLPosted today$180K
The opportunity
As a Specialist Solutions Architect (SSA) — AI/ML , you will serve as a trusted technical expert in Machine Learning and Artificial Intelligence for Databricks customers and our Field Engineering organization.
What you'll do
Architect AI/ML Workloads: Design and deploy production-level ML and AI architectures using the Databricks unified platform, including AI agents, end-to-end pipeline automation, and model training/inference optimization.
Lead GenAI Implementation: Act as a hands-on practitioner for enterprise Generative AI solutions, including Retrieval-Augmented Generation (RAG), tool-calling/multi-agent orchestration, guardrails, AI evaluation, and observability systems.
Optimize & Scale: Build and maintain scalable customer AI workloads, applying best-in-class MLOps practices across diverse industry domains.
Technical Pre-Sales Support: Partner with Solutions Architects during the sales cycle—guiding prospects through feature engineering, model tracking, serving, and monitoring within a single platform.
Influence the Product Roadmap: Translate customer feedback into actionable product insights by collaborating with Engineering and Product teams to shape the future of Databricks' AI offerings.
+ years of hands-on industry experience in at least one of the following: domains: ML Engineering: Building and maintaining cloud infrastructure (AWS, Azure, or GCP) supporting production ML applications and drift monitoring.
What they're looking for
- AI Engineering: Working with LLMs and agentic systems, including vector databases, fine-tuning, AI guardrails, and frameworks like LangChain, Hugging Face, or OpenAI APIs.
- Demonstrated ability to translate complex AI/ML concepts for both technical and non-technical audiences.
- Strong passion for continuous learning, cross-team collaboration, and: delivering tangible business value through AI.
- Understanding of modern lakehouse architectures (Delta Lake, data modeling,: BI integration) across major cloud platforms (AWS, Azure, or GCP).