Data AI · Lakehouse
Currently tracking 66 active AI roles, down 30% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $130k–$425k (avg $220k).
| Title | Stage | AI score |
|---|---|---|
| AI Engineer - FDE (Forward Deployed Engineer) AI Engineer (Forward Deployed Engineer) at Databricks focused on delivering professional services to help customers build and productionize GenAI applications. This role involves developing cutting-edge GenAI solutions, owning production rollouts, and serving as a technical advisor. | Agent | 8 |
| AI Engineer - FDE (Forward Deployed Engineer) AI Engineer (Forward Deployed Engineer) at Databricks focused on delivering professional services to help customers build and productionize GenAI applications. This role involves developing cutting-edge GenAI solutions, owning production rollouts, and serving as a technical advisor. | Agent | 8 |
| Resident Solutions Architect |
| — |
| 5 |
| Sr. Manager, Field Engineering Manager, Field Engineering (Solutions Architects) to build and lead a pre-sales team focusing on assigned accounts. Responsibilities include managing hiring, scaling the team, fostering a collaborative culture, supporting sales cycles, and building customer relationships. Requires experience in Pre Sales Manager roles with Big Data, Cloud, or SaaS, knowledge of data-driven decisions, AI, and Cloud software, and a background in Data Architecture. | — | 0 |
| Manager, Field Engineering Manager, Field Engineering (Solutions Architects) to build and lead a pre-sales team focusing on assigned accounts. Responsibilities include hiring, scaling the team, fostering a collaborative culture, increasing the ROI of SA involvement in sales cycles, and promoting value-based selling. Requires experience in Pre Sales Management with Big Data, Cloud, or SaaS professionals, scaling and mentoring technical teams, and background in Data Architecture. | — | 0 |
| Solutions Architect Solutions Architect role at Databricks focused on customer engagement, technical sales, and demonstrating the value of the Databricks Data Intelligence Platform. The role involves building client relationships, acting as a trusted advisor on architecture and implementation, and scaling best practices through reference architectures and demos. Requires proficiency in Big Data Analytics, coding in a core programming language, and experience with complex solution architecture designs. | — | 0 |
| Sr. Solutions Engineer This role is for a Sr. Solutions Engineer at Databricks, focusing on demonstrating the company's Data Intelligence Platform to clients. The role involves building client relationships, providing technical value, integrating with the cloud ecosystem, contributing to the technical community, and acting as a Big Data Analytics advisor. Responsibilities include authoring reference architectures and demo applications, with a path to becoming an independently operating Solutions Architect. The ideal candidate has client-facing experience, can deliver technical propositions, identify pain points, and has coding skills in Python, Java, or Scala, with knowledge in Big Data Analytics and public cloud platforms. | — | 0 |
| GTM Talent Sourcer (Contract) Databricks is seeking a Go-To-Market Talent Sourcer in Sydney, Australia, to find and engage top talent for roles including sales and solutions architects. The role involves developing sourcing strategies, nurturing talent pools, and using data to inform decisions. The ideal candidate will have 3+ years of technical or go-to-market recruiting experience and expertise in various sourcing techniques. | — | 0 |
| Field Engineering, Data Warehousing Product Specialist This role is a Field Engineering Product Specialist focused on Data Warehousing at Databricks. The primary responsibilities include defining and driving the technical go-to-market strategy in the APAC region, guiding customers on data warehousing architecture, acting as a trusted advisor to senior executives, and supporting internal field engineering teams. The role also involves partnering with Product Management to influence product direction and acting as a thought leader through external speaking engagements and content creation. Expertise in cloud-based data warehousing, modern data platforms, and traditional data warehousing techniques is required. | — | 0 |