About the company
CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025.
Responsibilities
- Drive the ongoing transition from monolithic to distributed architecture.
- Design and implement architecture to be agentic ready, enabling rapid deployment of AI products and MCP server integrations.
- Own technical decisions balancing immediate business needs with long-term architectural goals.
- Write production-quality Python code for critical platform components.
- Build and optimize distributed compute services.
- Implement reliable workflow orchestration patterns.
- Own CI/CD pipelines, automated testing, and deployment strategy for platform services.
- Drive reliability, observability, and SRE practices (monitoring, alerting, incident response, performance and scaling).
- Mentor senior and mid-level engineers, elevating the technical capabilities of the entire team.
- Establish engineering best practices and architectural patterns.
- Collaborate with product and business stakeholders to translate requirements into technical solutions.
- Guide technical decision-making and prioritization across multiple teams.
- Interview and onboard new engineers.
Requirements
- 10+ years of software engineering experience, including time in a staff-level engineering role.
- Broad software engineering depth spanning deployment and CI/CD, automated testing, and SRE/production reliability (observability, incident response).
- Deep expertise in distributed systems architecture, including building and operating large-scale distributed backend systems end-to-end.
- Strong API and service interface design skills for distributed services.
- Security-minded development, including authentication/authorization (e.g., OAuth) and secure-by-default practices.
- Expert-level Python development skills with production experience at scale.
- Strong Kubernetes experience with production workloads.
- Hands-on experience with workflow orchestration tools (Temporal, Airflow, Kubeflow, or similar).
- Cloud platform expertise (AWS required, Azure & GCP beneficial).
- Experience with data processing frameworks (Spark, Athena, Ray, or similar).
- Track record of driving architectural transformations in growing companies.
- Excellence in technical communication and stakeholder management.