Strategic Overview
Staff Software Engineer, Agentic Applications at Databricks is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Own the architecture and delivery of agentic workflows that enable marketing to self-serve content creation and publishing across blogs, landing pages, microsites, and social, working directly with marketing stakeholders to understand their workflows, define….
The role is listed for Mountain View, California with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
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.
Key Responsibilities & Objectives
- Own the architecture and delivery of agentic workflows that enable marketing to self-serve content creation and publishing across blogs, landing pages, microsites, and social, working directly with marketing stakeholders to understand their workflows, define quality criteria, and build tools they trust and use
- Partner with the Web Platform Staff Engineer on CMS architecture to ensure the content model supports agent read and write workflows and that agent-generated content is structured for AI-driven discovery at production scale
- Build and own the agent reliability system for this domain: define output quality criteria per workflow, implement eval suites and behavioral regression testing, and build feedback loops that improve agent output over time based on what marketers approve, edit, and reject
- Architect human in the loop review as a system property across the full publishing pipeline: proposal and commit separation, diff-based review UI, approval routing, notification system, and audit logging that govern when agents publish autonomously and when human judgment is required
Required Qualifications & Candidate Blueprint
- 12+ years of software engineering experience with a clear track record of technical ownership on production systems
- Hands-on experience building and operating LLM-powered systems in production, and a strong instinct for designing quality and evaluation frameworks for probabilistic or generative outputs
- Strong understanding of human in the loop system design: approval workflows, review interfaces, audit logging, and guardrail implementation
Salary & Benefits
Published compensation: $198,200 – $272,600 USD
Salary Benchmark
This role’s published compensation is compared with current employer-disclosed salary ranges for the same role at the Staff level in the same currency.
Benchmark uses active employer job postings in our database and excludes this listing. It is not a third-party salary estimate, and currencies are not converted.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
P-1578
About Us:
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.
The Role:
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.
The impact you’ll have:
- Own the architecture and delivery of agentic workflows that enable marketing to self-serve content creation and publishing across blogs, landing pages, microsites, and social, working directly with marketing stakeholders to understand their workflows, define quality criteria, and build tools they trust and use
- Partner with the Web Platform Staff Engineer on CMS architecture to ensure the content model supports agent read and write workflows and that agent-generated content is structured for AI-driven discovery at production scale
- Build and own the agent reliability system for this domain: define output quality criteria per workflow, implement eval suites and behavioral regression testing, and build feedback loops that improve agent output over time based on what marketers approve, edit, and reject
- Architect human in the loop review as a system property across the full publishing pipeline: proposal and commit separation, diff-based review UI, approval routing, notification system, and audit logging that govern when agents publish autonomously and when human judgment is required
- Encode brand, legal, and compliance constraints as enforceable guardrails within agent workflows, ensuring agents operate within defined boundaries without requiring human intervention on every decision
- Partner with the Web Products Staff Engineer to ensure agent-generated content meets surface quality and brand standards across databricks.com
- Mentor and grow the Senior Engineer on the team, setting the standard for production-grade agentic engineering at Databricks
What we look for:
- 12+ years of software engineering experience with a clear track record of technical ownership on production systems
- Hands-on experience building and operating LLM-powered systems in production, and a strong instinct for designing quality and evaluation frameworks for probabilistic or generative outputs
- Strong understanding of human in the loop system design: approval workflows, review interfaces, audit logging, and guardrail implementation
- Deep understanding of how agents interact with content systems, publishing pipelines, and web infrastructure including CMS, deployment pipelines, and edge delivery
- Ability to work directly with non-engineering stakeholders to translate workflow requirements into agent architecture
- Experience mentoring engineers and elevating technical execution across a team
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
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Own the architecture and delivery of agentic workflows that enable marketing to self-serve content creation and publishing across blogs, landing pages, microsites, and social, working directly with marketing… — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.