Specialist Solutions Architect - AI/ML
New
D
Databricks, Inc.Data and AI
Location: United States; This position can be remote.Full-TimeSenior
SalaryLocal Pay Range $180,000 — $247,500 USD
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Job Details
- Experience
- 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role
- Required Skills
- AWSPythonSQLGCPAzureDatabricksLLM
Requirements
- Bring 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role.
- Have ML engineering experience building and maintaining cloud infrastructure for production ML applications and drift monitoring.
- Have AI engineering experience with LLMs and agentic systems, including vector databases, fine-tuning, and AI guardrails.
- Demonstrate strong Python and SQL coding proficiency, including live coding, debugging, and solution building.
- Have deep expertise in distributed data systems architecture, including scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Be proficient on the Databricks Platform or able to achieve proficiency rapidly, with a developing technical specialization.
- Have experience leading architecture discussions with senior technical stakeholders, including whiteboarding, design reviews, and trade-off analysis.
- Have production deployment experience on AWS, Azure, or GCP, including infrastructure, security, and governance considerations.
- Show a track record of driving platform adoption and consumption growth within accounts.
- Hold a bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or have equivalent experience.
- Be willing to travel up to 30% as needed.
- Databricks certifications and experience with Snowflake, AWS native services, or Azure Synapse are nice to have.
Responsibilities
- Own end-to-end AI/ML technical strategy for accounts, from discovery through production deployment and consumption growth.
- Lead complex architecture discussions and design scalable, production-grade AI/ML solutions.
- Advise customer architects, engineering leads, and Directors on technical strategy.
- Demonstrate Databricks' differentiation through custom-built solutions in competitive scenarios.
- Develop a technical specialization and serve as a go-to resource for the team in that domain.
- Coordinate DSAs, SAs, and partners to deliver solutions for complex customer needs.
- Provide structured feedback on customer requirements and competitive gaps to influence product direction.
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