Senior Solutions Architect - AI & ML Engineer

About the role

Databricks is looking for a Senior Specialist Solutions Architect (SSA) - AI & ML Engineer in the Tel Aviv area, with a commute to the Herzliya office. As the trusted technical ML & AI expert for customers and the Field Engineering organization, you will work with Solution Architects to help enterprise and strategic customers design production-grade ML & AI applications on Databricks, aligning their roadmap with the Data Intelligence Platform. You will also mentor others and act as an AI thought leader.

Key responsibilities

• Architect production-level ML & AI workloads, including agents, end-to-end ML pipelines, training and inference optimization, and integration with cloud-native services and MLOps.
• Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems, natural language querying of structured data, AI evaluation and observability, and monitoring systems.
• Build, scale and optimize customer AI workloads, applying best-in-class MLOps to productionize them across domains.
• Provide advanced technical support to Solution Architects during technical sales, covering feature engineering, training, tracking, serving and model monitoring, and participate in the ML SME community.
• Work with product and engineering teams to represent the customer's voice, define priorities and influence the product roadmap.

Required profile

• 7+ years of hands-on industry ML experience, either as an ML Engineer or AI Engineer.
• Ability to communicate and teach technical concepts to both technical and non-technical audiences.
• Fluency in Hebrew and English.
• Preferred: 5+ years of customer-facing experience in a pre-sales or post-sales role, and the ability to meet technical training and role expectations within 3 months of hire.

Required skills

• ML Engineer: production-grade cloud infrastructure (AWS/Azure/GCP) supporting ML applications, including drift monitoring.
• AI Engineer: LLMs and agentic systems, vector databases, fine-tuning, AI guardrails, and tools such as HuggingFace, LangChain and OpenAI.
• Data engineering experience or a good understanding of the concept.