Staff AI Engineer Business Systems
Cerebras Systems, Inc.Visit Cerebras Systems, Inc. website
Cerebras builds wafer-scale AI computing systems and a cloud inference platform for training, fine-tuning, and serving AI models.
Sunnyvale, California, United States
About Cerebras Systems, Inc.
Cerebras Systems is an AI-infrastructure company founded in 2015. It sells rack-scale wafer-scale computing systems and provides cloud-based, API-accessible AI inference alongside on-premises deployments.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will design and build agentic solutions, orchestration services, enterprise applications, and reusable platform components. You will integrate approved business systems securely, evaluate AI platforms, establish production controls, and implement Finance, SOX, security, privacy, and audit requirements.
Requirements
- 8+ years in software, platform, integration, solution engineering, or enterprise applications
- Python and/or TypeScript
- Experience with APIs, MCP or comparable tool protocols, enterprise authentication, and distributed-system design
- Experience building production AI systems using agents, tool use, retrieval, structured outputs, evaluations, and monitoring
- Familiarity with LLM platforms and agent frameworks
- Solution-architecture judgment across security, reliability, performance, cost, observability, and supportability
- Knowledge of enterprise Finance processes
- Knowledge of compliance-by-design and audit evidence
Responsibilities
- Design end-to-end agentic solutions
- Translate stakeholder requirements into controlled AI workflows
- Create reusable architecture patterns for agents, tools, APIs, MCP servers, prompts, evaluations, and human-review workflows
- Build AI agents, orchestration services, enterprise applications, and platform components
- Establish secure AI connections to approved business systems
- Preserve authentication, authorization, entitlements, rate limits, and audit trails
- Refactor approved prototypes into monitored enterprise applications
- Establish release pipelines, incident response, and rollback controls
- Evaluate AI models, agent frameworks, connectors, and enterprise platforms
- Implement compliance, SOX, and audit controls