Senior Specialist Solutions Architect (ML & AI)

About the Role

Senior Specialist Solutions Architect (ML & AI) will serve as the trusted technical ML & AI expert for Databricks customers. You will partner with Solution Architects to guide enterprise and strategic customers in architecting production-grade ML and AI applications on the Databricks Data Intelligence Platform, while continuing to sharpen expertise in GenAI, ML, MLOps, and LLMOps and mentoring colleagues. What You'll Do

• Architect production-level ML and AI workloads, end-to-end pipelines, training/inference optimization, MLOps lifecycle management, and integration with cloud-native services.
• Lead GenAI initiatives: RAG architectures, agentic systems (tool-calling, multi-agent orchestration, guardrails), AI observability, and natural language querying of structured data; provide MVPs, deep-dive sessions, and ensure alignment with customer business challenges.
• Influence product roadmap by representing the voice of the customer and working cross-functionally with product and engineering teams.
• Drive thought leadership: tutorials, training materials, industry conferences, and hackathons to grow community and accelerate AI platform adoption. What We're Looking For
• Experience: 10+ years of hands-on DS/ML with a focus on either ML Engineering (production-grade cloud infrastructure for ML applications and monitoring) or Data Science/AI (LLMs, agentic systems, vector databases, fine-tuning, deployment tools such as HuggingFace, LangChain).
• Hands-on experience with distributed Spark-based systems.
• Experience with data engineering concepts or strong understanding of data engineering concepts.
• Pre-sales or post-sales experience working with external clients across various industries; minimum 5+ years of customer-facing experience preferred.
• Communication: proven ability to communicate and teach complex technical concepts to both technical and non-technical audiences.
• Education: graduate degree in a quantitative discipline or equivalent practical experience; able to meet expectations for technical training and role-specific outcomes within 3 months of hire.
• Can travel up to 30% when needed.
• [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets. Nice to Have
• [Preferred] Experience working with Apache Spark™ to process large-scale distributed datasets. Compensation & Benefits
• At Databricks, we provide comprehensive benefits and perks; regional details are available on request.