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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff AI Engineer - Business Systems - **Company:** Cerebras Systems - **Location:** Sunnyvale, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Microsoft Access, Application Programming Interfaces (APIs), Artificial Intelligence, Audit Trail, Business Systems, Python (Programming Language), Netsuite, Role-Based Access Control, TypeScript, Data Logging, Enterprise Software Applications, Delivery Pipeline, Large Language Models, Multi-Agent Systems, AI Platforms, Low Latency, Data Management, Code Restructuring, Automation Anywhere - **Published:** September 4, 2026 - **Apply:** https://www.dice.com/job-detail/8e890420-2df1-489f-ad67-9370cd409a94 ## About the Role Required capabilities are calibrated for a Staff-level hands-on engineer with solution-architecture responsibilities., * 8+ years in software, platform, integration, solution engineering or enterprise applications, including meaningful hands-on production ownership in complex environments. * Strong Python and/or TypeScript skills; experience with APIs, MCP or comparable tool protocols, enterprise authentication and distributed-system design. * Practical experience building production 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, including prompt and context engineering. * Strong solution-architecture judgment across security, reliability, performance, cost, observability and supportability. * Working knowledge of enterprise Finance processes such as general ledger, close, reporting, procure-to-pay, order-to-cash, forecasting and management reporting. * Working knowledge of compliance-by-design, including access, segregation of duties, change management, interfaces, automated controls, completeness and accuracy, and audit evidence. * Ability to communicate with engineers, Finance leaders, control owners, Security and executives. Preferred qualifications * Experience with ERPs, data platforms, frontier AI platforms, agent frameworks or comparable enterprise technologies. * Experience building internal enterprise applications. * Hands-on experience implementing SOX controls or operating in a public-company or audit-regulated environment. Success measures * Time from approved use case to controlled production and sustained adoption, with evidence of measurable business value. * Reduction in manual effort and business-process cycle time; improvement in decision quality or service levels. * Accuracy, groundedness, reconciliation success and production reliability of deployed agents. * User adoption, task success, stakeholder trust and support burden for production workflows. * Latency, operating cost and cost per successful task for deployed agents and applications. * Reuse of approved architecture patterns and components across use cases. ## Description The role is accountable for hands-on delivery and architecture within its layer, with shared governance across BIS, Finance, Business Operations, IT and Security and active partnership with other enterprise functions. AI solution architecture * Design end-to-end agentic solutions and determine when a use case should query a source system directly versus use the unified data model. * Partner with stakeholders to identify high-value use cases, translate 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. * Produce solution designs, security flows, deployment patterns and technical standards. AI engineering and system enablement * Build AI agents, orchestration services, enterprise applications and reusable platform components. * Deliver workflows for close and reporting, procurement, forecasting, billing and compliance monitoring where AI adds measurable value. * Establish secure, primarily read-only AI connections to approved business systems, beginning with NetSuite and extending to adjacent Finance and enterprise platforms as priorities evolve. * Preserve source-system authentication, authorization, user-level entitlements, rate limits and audit trails. * Implement citations, evidence links, deterministic checks, exception handling and safe action boundaries. Prototype-to-enterprise delivery * Assess business-built or rapidly developed prototypes for value, architecture, security, maintainability and control readiness. * Refactor or rebuild approved prototypes into tested, monitored and supportable enterprise applications. * Establish development, test and production environments, release pipelines, incident response and rollback controls. AI platform strategy * Evaluate AI models, agent frameworks, connectors and enterprise platforms on a regular cadence. * Run structured proofs of concept and assess security, accuracy, integration, scalability, experience, cost and vendor viability. * Maintain platform standards and recommend adoption, retention, replacement or retirement decisions. Organizational enablement and adoption * Create clear documentation, reusable patterns and reference architectures; coach teams on effective agent design, prompts, evaluation practices and safe operating boundaries. * Establish feedback loops with users and process owners; use adoption, task success, efficiency, trust and support signals to guide iteration. Finance, SOX and compliance * Translate Finance, Security, Privacy, SOX and SSDLC requirements into technical architecture and application controls. * Implement least privilege, segregation of duties, logging, retention, evaluation, change control and audit evidence. * Require deterministic validation and reconciliation for financially material outputs. * Support SOX walkthroughs, control testing, audits, risk assessments and remediation while escalating formal approval to control owners. ## Related Videos - [Swapping Low Latency Data Storage Under High Load](https://www.wearedevelopers.com/videos/746-swapping-low-latency-data-storage-under-high-load) - [Do TypeScript without TypeScript](https://www.wearedevelopers.com/videos/327-do-typescript-without-typescript) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Unleash the power of 5G in your code: transform your apps](https://www.wearedevelopers.com/videos/1567-unleash-the-power-of-5g-in-your-code-transform-your-apps) - [Vuejs and TypeScript- Working Together like Peanut Butter and Jelly](https://www.wearedevelopers.com/videos/127-vuejs-and-typescript-working-together-like-peanut-butter-and-jelly) - [Agents and AI in Enterprise - Dona Sarkar & Patrick Chanezon](https://www.wearedevelopers.com/videos/1893-agents-and-ai-in-enterprise-dona-sarkar-patrick-chanezon) ## Related Articles - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [What is Agentic Programming and Why Should Developers Care?](https://www.wearedevelopers.com/magazine/625-what-is-agentic-programming-and-why-should-developers-care)