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# Senior Software Engineer, AI Native Web Platform

- **Company:** Databricks
- **Location:** Mountain View, CA, United States
- **Experience:** Expert
- **Salary:** $159,900.0 - $219,900.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Code Generation, Continuous Integration, Key Management, Systems Development Life Cycle, Software Engineering, Web Engineering, Web Platforms, Delivery Pipeline, Deployment Automation, Build Tools
- **Published:** July 17, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f63e6c2c2e5cd823

## About the Role

* 8+ years of software engineering experience with a track record of shipping and operating production web infrastructure
 * Strong expertise across web platform infrastructure including CI/CD, deployment pipelines, build systems, and edge delivery
 * Experience implementing or operating consent management systems at the platform layer
 * Familiarity with accessibility standards and experience integrating automated a11y testing into CI pipelines is a strong plus
 * Ability to own a platform infrastructure domain end to end and drive it to production under Staff direction
 * Experience with tech stack consolidation or framework migration on live production systems is a strong plus

## Description

As Senior Software Engineer, AI Native Web Platform on the Web Engineering team, you will build and scale the platform layer that Web Engineering builds on: framework, infrastructure, CI/CD, and deployment pipelines. You will work under the direction of the Staff Software Engineer and contribute to a unified, agentic-ready foundation that shifts platform maintenance from per-surface effort to a centralized, scalable system., * Build and scale platform infrastructure including CI/CD pipelines, deployment automation, secrets management, and edge delivery configurations that power all of databricks.com

 * Own accessibility testing in CI, bringing automated a11y validation into the deployment pipeline so accessibility is enforced at every release rather than caught after the fact
 * Implement consent management infrastructure at the platform layer, replacing fragmented per-surface implementations with a centralized, policy-driven system that enforces compliance automatically across all web properties
 * Contribute to tech stack unification: consolidating a fragmented set of frameworks and deployment models onto a shared design system and unified deployment foundation
 * Operate in an AI native SDLC where agents assist across code generation, testing, and deployment, building faster and more reliably alongside them


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