Senior Backend Engineer, AI-Native Agentic Platform

Databricks; California (MO); On-site; USD 164,000 - 226,000; Full time

Job summary

Databricks is seeking a Sr. Backend Software Engineer for Customer Experience Intelligence (CXI) to architect and deliver an AI-native vertical workflow platform.

You will help design the enterprise Agentic Framework and scale workflows across domains, starting with customer support while enabling broader adoption. Role requires extensive backend development experience, deep distributed-systems knowledge, and hands-on ML-assisted backend work in multi-cloud environments (AWS, Azure, GCP).

Qualifications

• Extensive backend development experience designing, building, and maintaining high-throughput production systems.
• Deep familiarity with distributed systems and data platforms.
• Hands-on experience with ML-assisted backend systems and agentic workflows.

Responsibilities

• Architect and deliver Databricks' AI-native vertical workflow platform.
• Scale across multiple domains and optimize for Customer Support and other ticket-based workflows.
• Drive reliable backend development with strong quality, safety, throughput, and observability.
• Design state-machine and agentic workflows from human-in-the-loop to fully automated execution.
• Provide cross-functional leadership between CXI, Product, Platform Engineering, and stakeholders.

Skills

Backend development

Distributed systems

Multi-cloud (AWS/Azure/GCP)

LLM orchestration frameworks

Microservices

Education

BS in Computer Science or related engineering field

Job description

Databricks is seeking a Sr. Backend Software Engineer for Customer Experience Intelligence (CXI) to architect and deliver an AI-native vertical workflow platform.

You will help design the enterprise Agentic Framework and scale workflows across domains, starting with customer support while enabling broader adoption. Role requires extensive backend development experience, deep distributed-systems knowledge, and hands-on ML-assisted backend work in multi-cloud environments (AWS, Azure, GCP).