Staff Software Engineer - Customer Engagement & Docs Platform
Databricks · San Francisco, California
- Location
- San Francisco, California
- Level
- Staff
- Posted
- 12 January
About this role
Who we are
At Databricks, we are passionate about enabling data teams to 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 tackle 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.
Our AI-powered Assistant serves as the initial point of contact for customers seeking assistance on how to use our platform effectively. The Customer Engagement and Docs platform team's objective is to help customers resolve their problems faster using AI / LLMs. We provide customers with precise and comprehensive solutions to their problems or build experiences to facilitate a seamless escalation to a support agent when necessary.
As a Staff Engineer, you will operate at the intersection of Product development and Machine Learning. Responsibilities include gaining a deep understanding of user behavior; identifying factors contributing to problems; leveraging Product, Machine Learning (ML) and Large Language Models (LLMs) to analyze intricate technical use cases within a secure enterprise environment and eventually providing a path to resolving them.
The impact you will have:
- Lead design, development, and deployment of systems for Evaluation, Answer retrieval and Quality improvement for helping customers.
- Lead architectural decisions to ensure performance, reliability, and accuracy of the knowledge systems.
- Drive best practices for engineering excellence, including design reviews, code quality, testing strategies, and performance optimizations.
- Deliver high-quality, production-ready code and services end-to-end - including performance tuning, resiliency improvements, and debugging in live environments.
- Contribute to longer-term technical planning and support strategic initiatives in Assistant and Support organizations.
What we look for:
- 6+ years of industry experience building and operating large-scale distributed systems.
- Demonstrated technical proficiency in machine learning and software engineering, coupled with a strong product-oriented approach.
- The capacity to define and structure solutions in ambiguous problem domains.
- Ability to mentor and guide junior engineers, as well as to effectively collaborate across various team boundaries.
- Track record of driving high-impact, technically complex initiatives that delivered clear customer or business value.
- Prior experience with retrieval systems and search technologies is a plus.
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.
Local Pay Range$190,000-$260,000 USD
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.
As published by Databricks. Applications are handled on their site.
Skills this posting mentions
About Databricks
Databricks is the data + 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, Unity Gateway, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog.
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01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
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