Own the architecture and delivery of LLM-powered agents for marketing content workflows at Databricks.
Posted by employer 3 months ago
First seen on Joblaze 3 months ago
Last verified on the company career page 2 days ago
Role intensity
40% coding
AI in the day-to-day
Define how LLM-powered agents participate reliably across marketing content workflows.
Requirements
Not disclosed in this posting: work arrangement, visa sponsorship.
Joblaze summary
In the role of Staff Software Engineer for Agentic Applications at Databricks, the individual will architect and implement LLM-powered agents that streamline content creation and publishing for marketing. Key skills include extensive experience with production systems, LLM technologies, and human-in-the-loop design principles. This position is ideal for a seasoned engineer with a strong background in mentoring and cross-functional collaboration, particularly with non-technical stakeholders. The team is focused on building innovative, AI-driven workflows that enhance marketing efficiency and content quality.
Joblaze insights
Quick facts
From the original posting
P-1578
The Web Engineering team at Databricks builds and owns the public-facing web experiences that represent Databricks to the world, across databricks.com, the blog, landing pages, hubs, microsites, and event properties. We are rebuilding the platform from the ground up, AI native from the start, and pioneering an agentic SDLC as our operating model.
As Staff Software Engineer, Marketing Agents on the Web Engineering team, you will own the architecture and delivery of agents that transform how Databricks creates, publishes, and ships for the web, shifting content operations from a linear, engineering-dependent process to an orchestrated, continuously improving system. You will define how LLM-powered agents participate reliably across marketing content workflows, set the engineering standards the team builds on, and ensure agent output is robust, observable, and production-ready at scale.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. 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. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
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