Staff Software Engineer, AI-Powered Marketing Web

Databricks Inc.; Mountain View (CA); On-site; USD 198,200 - 272,600; Full time

Benefits offered by this job

Health, dental, vision benefis

Retirement plans

Paid time off

Job summary

Databricks Inc. is seeking a Staff Software Engineer, Agentic Applications for its Web Engineering team in Mountain View, CA. You will own the architecture and delivery of agentic workflows that transform how marketing content is created and published across blogs, landing pages, microsites, and social channels.

You will define how LLM-powered agents participate across content workflows, set engineering standards, and ensure agent output is robust, observable, and production-ready at scale.

Qualifications

• Hands-on experience building and operating LLM-powered systems in production.
• Strong understanding of human-in-the-loop design, review workflows and audit logging.
• Experience mentoring engineers and elevating technical execution across a team.

Responsibilities

• Own the architecture and delivery of agentic workflows enabling marketing to self-serve content creation and publishing.
• Partner with CMS architecture to ensure content models support agent read/write workflows and AI-driven discovery.
• Build the agent reliability system with evaluation suites and feedback loops from marketer approvals.
• Architect human-in-the-loop review across the publishing pipeline with diff-based review UI and audit logging.
• Encode brand, legal, and compliance guardrails within agent workflows.
• Collaborate with Web Products to meet surface quality and brand standards.
• Mentor and grow the Senior Engineer on the team.

Skills

LLM in production

Agentic systems

Mentoring engineers

Job description

Databricks Inc. is seeking a Staff Software Engineer, Agentic Applications for its Web Engineering team in Mountain View, CA. You will own the architecture and delivery of agentic workflows that transform how marketing content is created and published across blogs, landing pages, microsites, and social channels.

You will define how LLM-powered agents participate across content workflows, set engineering standards, and ensure agent output is robust, observable, and production-ready at scale.