AI and Automation Engineer - Business Systems

We Love AI Jobs; Sunnyvale, Northern (CA, KY); Hybrid; USD 180,000 - 260,000; Full time

Job summary

The AI and Automation Engineer for Cerebras Systems is a hands-on role in the Business Intelligence and Systems team in Sunnyvale. You will design, build, deploy and support production AI agents and reusable platform components to automate critical business workflows.

You will evaluate models and frameworks, set release thresholds, monitor performance, and partner with Finance, Accounting and Supply Chain to translate needs into secure, scalable automations within a Scrum/Agile process.

Qualifications

• Design, build, test, deploy and support production AI agents, orchestration services, enterprise applications and reusable platform components.
• Evaluate models, agent frameworks, connectors and enterprise platforms before production adoption.
• Partner with Finance, Accounting, Supply Chain, Business Operations, IT and Security to identify high-value use cases and translate requirements into controlled solutions.

Responsibilities

• Design and support secure connections between AI services and enterprise platforms (NetSuite, data, HR, CRM).
• Build reliable integrations using APIs, MCP, webhooks and enterprise platforms.
• Own operational requirements including credential rotation, access reviews, monitoring and incident response.

Skills

Python

TypeScript/JavaScript

AI agents and tool use

APIs and enterprise integrations

Model Context Protocol (MCP)

Retrieval and structured outputs

AI evaluations and monitoring

LangChain

Semantic Kernel

Tools

LangChain

Semantic Kernel

Model Context Protocol (MCP)

Job description

# AI and Automation Engineer - Business SystemsCerebrasSunnyvale, CA (Hybrid)Full-timeAI tools:OpenAIAnthropicGeminiLangChainSemantic KernelUpload your resume once and Scout applies for youApply with ScoutShare this job:LinkedInXSave imageBuilds and operates production AI agents, enterprise applications, and automations for Finance, Supply Chain, and other business teams. The engineer owns solutions from architecture and evaluation through security, deployment, and support, translating business processes into controlled and reliable workflows.* Permanent* Hybrid* 8+ years### Skills and expertisePythonTypeScript or JavaScriptAI agents and tool useAPIs and enterprise integrationsModel Context Protocol (MCP)Retrieval and structured outputsAI evaluations and monitoringLangChain and Semantic Kernel### Key responsibilities* Design, build, deploy, and support production AI agents, enterprise applications, and reusable platform components.* Evaluate models and agent frameworks, and create datasets, grading methods, release thresholds, and ongoing monitoring.* Partner with business teams to automate workflows while implementing security, compliance, and financial controls.## How this job comparesCompared with 410 open senior machine learning jobs on October 10, 2026.Pay: This job does not publish its pay. The 143 open senior machine learning jobs that publish US pay start at $186K a year on average.Similar open jobs: We Love AI Jobs lists 410 open senior machine learning jobs at 176 companies.Remote work: This job is hybrid. 90 of the 410 senior machine learning jobs (22%) are remote.AI in this role: High. AI is the core of the work: building, training or deploying AI systems. Building, evaluating, deploying, and supporting production AI agents is the core of the role. The posting calls for hands-on work with agents, retrieval, tool use, evaluation, and named LLM platforms and frameworks.## Full descriptionCerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.Hands-on AI engineering, enterprise automation and agile delivery for Finance, operations and business systemsAbout the roleThe AI and Automation Engineer is a hands-on member of the Business Intelligence and Systems team responsible for designing, building and operating secure AI solutions and enterprise automations for Cerebras. The role will translate complex Finance, Accounting, Supply Chain and enterprise requirements into reliable agents, applications, integrations and controlled workflows.This engineer will serve as a technical owner across the AI and automation lifecycle. The role combines solution architecture with direct engineering, disciplined production support, and delivery through Scrum and Agile practices. Success requires strong software-engineering judgment, practical business-process knowledge and the ability to move a prototype into a secure, tested and supportable production service.What you will doAI solution architecture and engineering• Design, build, test, deploy and support production AI agents, orchestration services, enterprise applications and reusable platform components.• Create reusable patterns for agents, tools, APIs, 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, HR, CRM and other systems as priorities evolve.• Build reliable integrations using APIs, MCP, webhooks, event-driven services, SFTP 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.AI platform evaluation and production reliability• 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.Business process solutions and adoption• Partner with Finance, Accounting, Supply Chain, Business Operations, IT 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.Scrum and Agile delivery• Deliver work through a Scrum-based operating model, participating actively 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.