TL;DR
Manager of Business Operations at Cerebras Systems, building operational analytics and execution systems for AI chip manufacturing and deployment. Role combines analytics infrastructure, KPI design, and process improvement across supply chain and data center operations.
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top 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.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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.
About The Role
This role is a high-leverage seat in that build and a deliberate apprenticeship into operating leadership. You will create the business operations, analytics, and execution system that keeps decision-ready insight flowing as the company scales. You will be embedded with operators, turning messy operational reality into durable processes, clear metrics, and repeatable operating rhythms. You will report to the Head of FP&A and work in close partnership with the COO and operations leadership.
Why now
Cerebras is scaling to meet accelerating demand for fast inference. That growth forces rapid expansion across supply chain, manufacturing, and data center deployment. The company needs closed-loop processes and trusted insight assets that scale with the business and remain durable under increasing scrutiny.
Recent market validation, including a marquee partnership with OpenAI, is an early signal of a broader shift: fast inference is becoming foundational, and it is still early days. Operational excellence will compound, and the systems built now will define how efficiently the company scales.
Role at a glance
- Partner with 5 to 10 operational leaders across supply chain, manufacturing, and data center deployment to drive insight and action.
- Own and deliver the right information in the right way at the right time. Build the context that allows the organization to know what happened, the implications, and what to do next.
- Drive closed-loop operational change. Diagnose bottlenecks, redesign processes, and follow through until adoption and measurable improvement are real.
- 50/50 analytics and execution. You build the assets (metrics, dashboards, operating packets) and you drive the behaviors (cadence, accountability, decisions).
- Apprenticeship into operating leadership. We mean it. The hiring manager has used this model repeatedly over the years and can provide references from alumni who have enjoyed meaningful career acceleration.
- Elegant entry point in the cutting edge of AI. If your pace, horsepower, agency, and ambition are elite, this role gives you room to run.. If you make an impact you can chart your own path.
- Small, elite, high-standards team. You are a hands-on leader who learns fast, raises the pace, and may selectively add exceptional talent over time to amplify leverage. This will be a small and mighty team.
What you will build
- Operational analytics infrastructure required to scale supply chain, manufacturing, inventory management, and data center operations with uncompromising quality and speed.
- A decision-quality KPI and reporting architecture: leading indicators, dashboards, recurring reviews, and crisp narratives that operators trust.
- Closed-loop mechanisms that turn operational complexity into repeatable processes: metric definitions, data ownership, reconciliation paths, and accountability loops.
- System integration between operational data sources and finance systems so that decisions are grounded in consistent, auditable definitions.
- Automation and tooling that compounds output, including structured data pulls, workflow automation, and pragmatic use of AI tools to reduce manual work.
- Public-company-ready operating rhythms: clean close-to-insight timelines, documented definitions, and durable operating packets that scale with scrutiny.
What you will own
- Operations partnering: Work shoulder-to-shoulder with operations leadership to translate operational reality into clear priorities, tradeoffs, and actions.
- KPI standards and insight assets: Define the metrics that matter, build the dashboards and operating packets, and keep them accurate as systems and processes evolve.
- Operating cadence: Design and run weekly and monthly performance reviews, ensure decisions are made, and close the loop on follow-through.
- Process change: Identify the highest-leverage process gaps, drive redesign and adoption, and measure impact in throughput, cycle time, quality, and predictability.
- Data quality and reconciliation: Build trust in the numbers by instituting clear definitions, checks, and ownership across operational and finance systems.
- Executive communication: Deliver concise narratives that clearly separate signal from noise and drive action.
What success looks like in the first 6 to 12 months
- You earn trust. Operators proactively pull you into decisions because your work improves outcomes, not just visibility.
- You grow as an operator. You turn consulting-grade problem solving into operating judgment, cross-functional credibility, broader ownership and ultimately IMPACT.
- Durable insight assets are live (dashboards, weekly and monthly operating packets, KPI definitions) with a clear cadence and single-source-of-truth inputs.
- A small number of critical operational processes are redesigned and adopted, with measurable improvements in speed, predictability, and execution quality.
- Cross-functional decisions move faster because the organization shares consistent definitions and a clear view of tradeoffs and constraints.
- Manual reporting load declines materially as automation and self-serve assets replace ad hoc requests and one-off analyses.
What we are looking for
We are hiring for horsepower, motor, agency, and systems thinking. Horsepower means exceptional analytical ability. Motor means a high pace of work. Agency means you identify what the business needs next, build it, and bring others along.
- 6 to 10 years of total experience is a reasonable guide. We will bias toward demonstrated impact and judgment over years.
- 2+ years at a top-tier strategy consulting firm (McKinsey, BCG, Bain, or similar), with readiness to turn generalist problem-solving into company operating impact.
- Experience driving operational change inside a scaling company. This can come from operations, strategy, analytics, or FP&A, as long as you have owned real outcomes.
- High learning velocity. You want an apprenticeship, not just a title, and you learn quickly from direct feedback while owning real outcomes.
- Strong analytical skills and comfort with imperfect data. You can go from ambiguity to a clear framework, then execute.
- High agency. You do not wait for perfect inputs or perfect direction. You move, communicate, and close loops.
- Systems thinker. You build infrastructure that continues working when the pace increases and the data gets messy.
- Technical fluency beyond spreadsheets (preferred). Comfortable with SQL, Python, or adjacent tooling to pull and shape data and automate recurring work.
- Clear executive communication. You distill complexity into concise narratives that drive decisions.
- AI affinity. You proactively apply modern tools to speed up workflows, improve quality, and reduce manual work.
Ways to stand out
- Experience in hardware, semiconductor, manufacturing, supply chain, or data center operations.
- Comfort with Python or similar tooling as evidence of your ability to be a leading creator and user of agents
- A track record of building KPI architectures, operating cadences, and repeatable mechanisms from scratch.
- Experience partnering directly with COO, C-suite, or VP-level operational leaders.
- Demonstrated pattern of high agency: you see problems early and fix them before being asked.
Why Join Cerebras
People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source their cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- Our simple, non-corporate work culture that respects individual beliefs.
Read our blog: Five Reasons to Join Cerebras in 2026.
Apply today and become part of the forefront of groundbreaking advancements in AI!
Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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