Sr. Specialist Solutions Architect

Databricks
Melbourne, Sydney
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: mastersSkills: ["Communication","Teaching","Collaboration","Mentorship","Life-long learning"]

Serve as a trusted technical ML & AI expert to customers and Databricks Field Engineering. Architect production-grade ML & AI workloads on the Databricks Data Intelligence Platform, including agents, end-to-end pipelines, optimization, and MLOps. Support technical sales with deep expertise across feature engineering, training, serving, monitoring, and GenAI patterns such as RAG and agentic systems. Collaborate with product and engineering to shape priorities and roadmap adoption.

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FursaFursa
Databricks
Databricks
3 days ago

Sr. Specialist Solutions Architect

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Source: Company careers pageValidated by: Fursa AI
Last checked: 20 hours agoStatus: Live

Job Summary

Serve as a trusted technical ML & AI expert to customers and Databricks Field Engineering. Architect production-grade ML & AI workloads on the Databricks Data Intelligence Platform, including agents, end-to-end pipelines, optimization, and MLOps. Support technical sales with deep expertise across feature engineering, training, serving, monitoring, and GenAI patterns such as RAG and agentic systems. Collaborate with product and engineering to shape priorities and roadmap adoption.
Location: Melbourne, Sydney
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Architect production-level ML & AI workloads for customers, including agents, end-to-end pipelines, and training/inference optimization on a unified platform.
  • •Act as a trusted practitioner for enterprise GenAI solutions such as RAG architectures, agentic systems, tool-calling agents, multi-agent orchestration, guardrails, and AI evaluation/observability.
  • •Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize across domains.
  • •Provide advanced technical support to Solution Architects during technical sales across the ML lifecycle: feature engineering, training, tracking, serving, and model monitoring.
  • •Collaborate with product and engineering to represent the voice of the customer, define priorities, influence the product roadmap, and support adoption of Databricks AI offerings.
Travel: High travel

Key Requirements

  • •5+ years of hands-on industry ML experience in cloud-based ML engineering, AI/LLM & agentic systems, or both.
  • •Experience deploying and operating production-grade ML/AI infrastructure on AWS, Azure, or GCP, including drift monitoring.
  • •Experience with LLM techniques such as vector databases, fine-tuning, and AI guardrail systems, and deploying LLMs with HuggingFace, LangChain, and OpenAI.
  • •Graduate degree in a quantitative discipline (or equivalent practical experience).
  • •Ability to communicate and/or teach technical concepts to technical and non-technical audiences.
Experience:5+ yearsMLAIGenAIMLOpsCloud-nativeLLMsAgentic systemsPre-salesPost-sales
Education:Master's in Quantitative discipline (e.g., Computer Science, Engineering, Statistics, Operations Research)
Skills:CommunicationTeachingCollaborationMentorshipLife-long learning
Languages:English
Tech Stack:AWSAzureGCPGenAIMLMLOpsLLMsRAGVector databasesFine-tuningAI guardrail systemsHuggingFaceLangChainOpenAIAgentsMulti-agent orchestrationTool-calling agents

Company Brief

Databricks
Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn