Staff Software Engineer, Sales Data & Agents

About the role

CRM is where revenue teams record their work, however they generally lack a solid intelligence layer. Objects are customized past recognition, history is incomplete, and reps route around whatever slows them down. As a result, the sales intelligence layer increasingly lives in a Data+AI platform. We are looking to productize with data & agents what our customers have been already manually building in our platform.

Responsibilities

• Lead the modeling of sales/CRM objects, relationships, and history into a representation agents can reason over reliably
• Lead development of agents used by reps, sales management, and revenue operations
• Define the write path back into the system of record: permissions, validation, idempotency, audit, and human approval
• Help define & lead the implementation of the initial use cases on top of the data & agents
• Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth
• Create novel, never-seen-before interfaces for GenAI agents that manage complex workflows while keeping the human in the loop through inspectability and transparency

Requirements

• 10+ years of engineering experience, including time as a tech lead, or leading other tech leads, on complex enterprise software projects
• Deep hands-on knowledge of at least one major CRM data model and platform (Salesforce, Dynamics, HubSpot): objects, sharing and permission models, history tables, bulk and change-data APIs, platform limits
• Real understanding of how reps and managers use these tools day to day, and where forecasting, pipeline hygiene, and territory data break down
• Experience shipping production agents with tool use, permissioned writes, and human-in-the-loop review
• High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption
• Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives
• Demonstrated product mindset with the ability to translate ambiguous customer problems into scrappy MVPs and iterate quickly based on data and user feedback
• Combination of technical and people leadership, for example, as a TLM

Nice to have

• Built revops, forecasting, or CPQ-adjacent products
• Time spent in-house on a Salesforce platform team or at an SI

Pay

Local Pay Range: $190,900—$253,750 USD

Databricks is committed to fair and equitable compensation practices. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. For more information regarding which range your location is in visit our page here.