Staff AI Engineer – Business Systems
Cerebras Systems1 month ago
Responsibilities
- Design end-to-end agentic solutions and determine whether use cases should query source systems directly or use a unified data model.
- Translate stakeholder requirements into controlled AI workflows and select AI, conventional automation, or no new technology.
- Create reusable architecture patterns for agents, tools, APIs, MCP servers, prompts, evaluations, and human-review workflows.
- Build AI agents, orchestration services, enterprise applications, and reusable platform components for Finance and business operations.
- Establish secure connections to approved business systems, beginning with NetSuite, while preserving authentication, authorization, user entitlements, rate limits, and audit trails.
- Implement citations, evidence links, deterministic checks, exception handling, reconciliation, and safe action boundaries.
- Assess prototypes and refactor or rebuild approved solutions into tested, monitored, supportable enterprise applications.
- Establish development, test, and production environments, release pipelines, incident response, and rollback controls.
- Evaluate AI models, agent frameworks, connectors, and enterprise platforms through structured proofs of concept and make platform adoption recommendations.
- Document architecture patterns, coach teams on agent design and evaluation practices, and guide adoption using user and process feedback.
- Translate Finance, Security, Privacy, SOX, and SSDLC requirements into technical architecture and application controls while supporting walkthroughs, audits, risk assessments, and remediation.
Requirements
- 8+ years of experience in software, platform, integration, solution engineering, or enterprise applications, including meaningful hands-on production ownership in complex environments.
- Strong Python and/or TypeScript skills with experience in APIs, MCP or comparable tool protocols, enterprise authentication, and distributed-system design.
- Production experience building AI systems using agents, tool use, retrieval, structured outputs, evaluations, and monitoring.
- Practical familiarity with leading LLM platforms and agent frameworks such as OpenAI, Anthropic, Gemini, LangChain, Semantic Kernel, or comparable technologies.
- Strong solution-architecture judgment across security, reliability, performance, cost, observability, and supportability.
- Working knowledge of enterprise Finance processes including general ledger, close, reporting, procure-to-pay, order-to-cash, forecasting, and management reporting.
- Working knowledge of compliance-by-design, access controls, segregation of duties, change management, interfaces, automated controls, completeness and accuracy, and audit evidence.
- Ability to communicate effectively with engineers, Finance leaders, control owners, Security, and executives.
- Preferred experience with ERPs, data platforms, frontier AI platforms, agent frameworks, internal enterprise applications, SOX controls, or public-company and audit-regulated environments.
Benefits
- Opportunity to build a breakthrough AI platform beyond GPU constraints and work on a fast AI supercomputer.
- Opportunities to publish and open source cutting-edge AI research.
- Job stability with startup vitality and a simple, non-corporate work culture.
- Cerebras is committed to an equal and diverse work environment with continuous learning, growth, and support.
Tech Stack
Categories
About Cerebras Systems
Cerebras Systems designs and sells AI compute systems built around its wafer-scale WSE-3 processor, delivered as the CS-3 appliance and via the Cerebras Cloud. It targets enterprises, model labs, and government users needing fast training and inference, and offers on‑prem and cloud deployments. Privately held and headquartered in Sunnyvale, California, the company announced a multi-year partnership with OpenAI to deploy large-scale inference capacity.