Specialist Solutions Architect - AI/ML

FEQ427R382

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. Working

This role offers an opportunity to work at the forefront of cutting-edge technologies—including Generative AI, LLMs, and MLOps—while mentoring peers and establishing yourself as a technical thought leader in the AI community.

The impact you will have:

• 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.

What we look for:

• 5+ 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.
    
  • 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).
• [Preferred] Prior experience in a pre-sales or post-sales technical consulting role.
• Graduate degree in Computer Science, Engineering, Statistics, or a related quantitative field—or equivalent practical experience.
• Ability to travel up to 30% as needed for customer engagements.
• Ability to hit role-specific training and technical delivery milestones within the first 6 months.
• Ability to travel up to 30% as needed for customer engagements.