Build and evolve the Neo4j Graph Analytics for Snowflake application, embedding Neo4j Graph Data Science into the Snowflake platform.
Responsibilities
Build and evolve the Neo4j Graph Analytics for Snowflake application, embedding Neo4j Graph Data Science into the Snowflake platform.
Design and improve our SQL-facing API: stored procedures, UDFs, and the surface area customers call from their warehouses.
Own significant parts of the build, release, and deployment pipeline: Snowflake CLI, Gradle, container images, and the Java/Python runtimes that execute inside Snowpark Container Services.
Improve the platform's security posture: caller's rights vs. owner's rights stored procedures, restricted caller's rights (RCR), grants, and proactive image scanning.
Collaborate with customers and Solution Engineers to turn real-world requirements into scalable features.
Build backend services, platform infrastructure, and AI capabilities that power next-generation agentic applications for Snowflake’s Go-To-Market organization.
Compensation
The estimated base salary range for this role is $156,000 - $224,200. Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan. The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
Responsibilities
Design and build scalable backend services and distributed systems that power production AI and agentic applications.
Develop APIs, orchestration services, and platform capabilities for internal AI products.
Build reusable AI platform components, including agent frameworks, evaluation pipelines, developer SDKs, templates, and shared Python libraries.
Evolve our engineering platform through modern CI/CD pipelines, automated testing, deployment tooling, and developer experience improvements.
Optimize AI infrastructure and backend services for performance, scalability, reliability, security, and cost efficiency.
Requirements
Bachelor's degree in Computer Science, Software Engineering, or a related technical field
Architecting and implementing cloud-based data warehousing, lakehouse, analytics and AI solutions on the Snowflake AI Data Cloud and selected major cloud providers.
Responsibilities
Architecting and implementing cloud-based data warehousing, lakehouse, analytics and AI solutions on the Snowflake AI Data Cloud and selected major cloud providers (Microsoft, GCP, AWS).
Defining best practices for data governance, security, performance optimization, and cost efficiency in Snowflake environments, including Horizon Catalog and governed, auditable access for AI agents.
Collaborating with cross-functional teams (data engineers, data scientists, AI engineers, and cloud architects) to deliver end-to-end data platform and AI solutions.
Integrating Snowflake with broader cloud ecosystems, including open lakehouses (Apache Iceberg), data integration and streaming services (Openflow, Snowpipe Streaming), AI/ML frameworks, and visualization tools.
Using Snowflake CoCo, Snowflake’s AI coding agent, to accelerate delivery of SQL, dbt models, pipelines and AI applications, and defining guardrails, reusable skills and review practices for AI-assisted development.
