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Cerebras

AI accelerator hardware replacing GPUs

AI and Automation Engineer - Business Systems

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeSunnyvale, CA, USANo salary listedHybrid

About the Job

Requirements

  • At least 8 years of experience in software, platform, integration, solution engineering, enterprise applications, or related technical roles, including hands-on production ownership in complex environments.
  • Strong Python and TypeScript or JavaScript skills, with practical experience building APIs, services, and enterprise applications.
  • Hands-on experience building production AI systems using agents, tool use, retrieval, structured outputs, evaluations, and monitoring.
  • Practical experience with leading large language model platforms and agent frameworks such as OpenAI, Anthropic, Gemini, LangChain, Semantic Kernel, or comparable technologies.
  • Experience designing integrations with Model Context Protocol or comparable tool protocols, enterprise authentication, permission-aware access, and distributed-system reliability patterns.
  • Ability to design and build complete solutions rather than only evaluate vendors, administer platforms, or produce prototypes.
  • Working knowledge of enterprise Finance processes, including close, reporting, procure to pay, order to cash, forecasting, and management reporting.
  • Experience working in Scrum or Agile teams and translating requirements into appropriately sized stories, estimates, acceptance criteria, test plans, and releases.
  • Working knowledge of software engineering practices, including version control, peer review, environment management, automated testing, continuous integration and continuous delivery, and observability.
  • Analytical, troubleshooting, and communication skills to work effectively with business leaders, engineers, Security, control owners, and external partners.

Responsibilities

  • Design, build, test, deploy, and support production AI agents, orchestration services, enterprise applications, and reusable platform components.
  • Create reusable patterns for agents, tools, application programming interfaces, Model Context Protocol servers, prompts, retrieval, evaluations, and human-review workflows.
  • Design and support secure connections between AI services and approved enterprise platforms, beginning with NetSuite and extending to data, procurement, contracts, human resources, customer relationship management, and other systems as priorities evolve.
  • Build reliable integrations using application programming interfaces, Model Context Protocol, webhooks, event-driven services, secure file transfer protocol, and enterprise integration platforms where appropriate.
  • Own operational requirements for internal and third-party components, including credential and key rotation, access reviews, patching, monitoring, incident response, and recovery.
  • Evaluate models, agent frameworks, connectors, and enterprise platforms through structured proofs of concept and documented technical recommendations.
  • Assess accuracy, security, reliability, integration fit, user experience, latency, operating cost, and vendor viability before production adoption.
  • Build evaluation datasets, automated and human grading methods, release thresholds, and ongoing monitoring for deployed solutions.
  • Diagnose production failures, identify root causes, and implement durable improvements to code, prompts, data, controls, and operating procedures.
  • Partner with Finance, Accounting, Supply Chain, Business Operations, Information Technology, and Security to identify high-value use cases and translate requirements into controlled solutions.
  • Deliver solutions for close and reporting, forecasting, procurement, billing, compliance monitoring, and other enterprise workflows where automation provides measurable value.
  • Establish clear business ownership, user feedback loops, training, and adoption plans for every production workflow.
  • Use task success, accuracy, business-process cycle time, adoption, trust, and support demand to guide iteration and determine whether a solution should scale.
  • Deliver work through a Scrum-based operating model, actively participating in backlog refinement, sprint planning, daily stand-ups, estimation, demonstrations, and retrospectives.
  • Convert business needs into epics, user stories, technical tasks, acceptance criteria, evaluation plans, and sequenced releases.
  • Break complex initiatives into testable increments and communicate scope, dependencies, risks, tradeoffs, and delivery status clearly.
  • Maintain a definition of done covering design approval, peer review, testing, security and control validation, documentation, deployment readiness, and operational handoff.
  • Translate Security, Privacy, Sarbanes-Oxley, and Secure Software Development Lifecycle requirements into technical architecture, application controls, and operating procedures.
  • Implement least privilege, segregation of duties, logging, retention, change control, evidence collection, and periodic access review.
  • Require deterministic validation and reconciliation when AI or automation touches financially material data or calculations.
  • Support control walkthroughs, testing, audits, risk assessments, and remediation while preserving formal approval by the appropriate control owner.

Desired Qualifications

  • Experience building AI or automation solutions for Finance, Accounting, Supply Chain, or other controlled enterprise processes.
  • Experience integrating AI services with enterprise resource planning, data, procurement, contract, human resources, customer relationship management, or enterprise workflow platforms.
  • Experience with cloud platforms, event-driven or serverless architectures, and enterprise integration platforms.
  • Experience implementing Sarbanes-Oxley controls or operating in a public-company, initial-public-offering-readiness, or audit-regulated environment.
  • Experience in semiconductor, hardware, manufacturing, or another operationally complex environment.

About the Company

Cerebras

AI accelerator hardware replacing GPUs

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company size
501-1,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2016

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