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Senior AI Engineer, Enterprise
Summary by AIEngineer.careers
Senior AI Engineer, Enterprise is a AI Engineer role (full-time). with snowflake. in MENLO PARK, US. Compensation shown: $156K–$224K. Imported listing (source: 1profile.app). Apply on the employer's site (1profile.app).
Imported listing (source: 1profile.app) · Apply on 1profile.app
MENLO PARK · US
$156K–$224K
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from 1profile.app
Snowflake is seeking a Senior AI Engineer to join its GTM AI Engineering team, building internal AI platforms and intelligent applications for the Go-To-Market organization. You will design scalable backend services, distributed systems, and AI capabilities that power production agentic applications used by thousands of employees. This role sits at the intersection of distributed systems, backend engineering, and applied AI, with a focus on reliability, security, and business impact.
Responsibilities
- Design and build scalable backend services and distributed systems for 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 the 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.
- Leverage Snowflake Cortex, Snowpark, and the broader Snowflake AI ecosystem to build intelligent data applications.
- Establish engineering best practices around testing, observability, monitoring, evaluation, and production readiness for AI systems.
snowflake
Menlo Park · US · 9250+ employees
Snowflake Inc. is a cloud-based data platform company that provides a fully managed service for data warehousing, data lakes, data engineering, and data sharing. Its architecture enables customers to consolidate data for analytics, AI applications, and secure data exchange across major public cloud infrastructure.
