Applied AI Architect
Databricks5 days ago
Base Salary
$180k - $248k/yr
Responsibilities
- Own end-to-end AI/ML technical strategy for customer accounts from discovery through production deployment and consumption growth.
- Lead architecture discussions for scalable production solutions involving RAG, tool calling, multi-agent orchestration, guardrails, AI evaluation, and observability systems.
- Serve as a trusted technical advisor to customer architects, engineering leads, and Directors.
- Drive technical wins through custom-built solutions that demonstrate Databricks differentiation.
- Develop a technical specialization and become a go-to resource within the Field Engineering team.
- Orchestrate DSAs, SAs, and partners to deliver comprehensive solutions.
- Provide structured customer and competitive feedback to influence product direction.
Requirements
- 6+ years of experience in solutions architecture, technical pre-sales, or a senior hands-on technical role.
- Experience with ML engineering, cloud infrastructure for production ML applications, and drift monitoring.
- Experience with LLMs and agentic systems, including vector databases, fine-tuning, AI guardrails, and relevant frameworks or APIs.
- Strong coding proficiency in Python and SQL, including live coding, debugging, and solution building.
- Deep expertise in distributed data systems, scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Proficiency with the Databricks Platform or the ability to become proficient rapidly, with a developing specialization in an area such as real-time/streaming, ML/AI, data governance, or migrations.
- Experience leading architecture discussions, whiteboarding, design reviews, and trade-off analysis with senior technical stakeholders.
- Production deployment experience on AWS, Azure, or GCP, including infrastructure, security, and governance considerations.
- Track record of driving platform adoption and account consumption growth.
- Excellent communication skills for translating complex architectures into business value for technical and executive audiences.
- Bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
- Databricks certifications and experience with Snowflake, AWS native services, or Azure Synapse are preferred.
- Experience in a data/AI company or cloud provider and industry domain expertise are preferred.
Benefits
- Remote position.
- Willingness to travel up to 30% as needed.
- Benefits and perks are provided, with region-specific details available from Databricks.
- Potential eligibility for an annual performance bonus and equity in addition to benefits.
Tech Stack
Categories
Solutions Engineering
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.