IT Solutions Tech Lead (Staff Fullstack SWE)

GAQ225R147

Location: San Francisco, CA or Mountain View, CA

At Databricks, we are passionate about helping data teams solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and customer-obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

At Databricks Information Technology, we are a product-led organization transforming the way we work, from how easy it is to use our IT services to the applications we develop that help us scale seamlessly in the face of incredible growth. 

The impact you will have:

• Architect complex solutions that integrate AI-powered features such as chatbots, virtual assistants, predictive recommendations, and agentic workflows.
  
  
• Design, develop, manage, and deploy scalable full-stack applications on cloud-native, distributed systems with embedded AI capabilities.
  
  
• Prototype and productionize AI use cases using tools like LLMs, vector databases, prompt engineering, and agentic workflows.
  
  
• Collaborate with Product Managers, UX Designers, Enterprise Security, Data Teams, and Integration Teams to deliver secure, scalable, AI-driven solutions.
  
  
• Mentor peers on best practices in full-stack development, cloud architecture, and AI technologies, helping to shape the team’s technical roadmap.
  
  
• Stay ahead of the curve by continuously researching and experimenting with emerging AI trends, frameworks, and tools to drive innovation.

 

What we look for:

• 8 years of related experience with both front-end tools like ReactJS, Django, and backend stack such as Java, Go, and Python

 

• Experience developing scalable, secure, and resilient applications
  
  
• Hands-on experience building AI-powered solutions, including projects involving Generative AI (LLMs, agentic frameworks, Vector Search, prompt engineering etc.) or other machine learning technologies.
  
  
• Experience building integrated solutions with SaaS platforms such as Salesforce, Workday, ERP, etc.
  
  
• Strong experience with cloud technologies (AWS, Azure, or GCP), along with a solid grasp of DevOps practices and CI/CD pipelines.

 

• Demonstrated experience in design practices, code reviews, automated testing, and monitoring/logging

 

• Deep understanding of security best practices, including systems that process sensitive or regulated data.
  
  

 

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.

 

Zone 1 Pay Range$173,100—$242,400 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Benefits