Specialist Solutions Architect - AI/ML
Databricks · United States · Field Engineering - FE Direct Regulated
About this role
Databricks is hiring a mid-level Solutions Architect in the software engineering function based in United States. The posting calls out experience with AWS, GCP, Azure, Spark. Compensation is listed at $180,000–$247,500 per year.
- Role
- Solutions Architect
- Function
- software engineering
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- United States
- Department
- Field Engineering - FE Direct Regulated
More roles at Databricks
Job description
from Databricks careersFEQ227R247
As a Specialist Solutions Architect (SSA) - AI/ML Engineering, you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying cutting-edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader. This role can be remote.
The impact you will have:
- Architect production-level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.
- Serve as a trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems
- Build, scale, and optimize customer AI workloads and apply best-in-class MLOps to productionize these workloads across a variety of domains
- Provide advanced technical support to Solution Architects during the technical sale, ranging from feature engineering, training, tracking, serving, to model monitoring, all within a single platform, as well as participating in the larger ML SME community in Databricks