AI Engineer - Forward Deployed Engineering (AI FDE)

AI Engineer - Forward Deployed Engineering (AI FDE)

Mission

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications.

We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team.

This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. Open to remote locations.

This role is intended for experienced engineers with demonstrated industry experience designing, building, and deploying production GenAI and LLM applications at scale. It is not intended for internship, new graduate, or entry-level applicants.

The impact you will have

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from Databricks AI research to solve customer problems
• Own production rollouts of consumer and internally facing GenAI applications
• Serve as a trusted technical advisor to customers across a variety of domains
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

What we look for

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
• Passion for collaboration, life-long learning, and driving business value through AI
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets
• Willing to travel once every 4-8 weeks to see customers (as needed)

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 $152,900—$210,155 USD

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

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.