Parasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.
We’re hiring the first Capacity & Infrastructure Operations Manager to own the operational and analytical “supply-side” of our GPU fleet. You will partner closely with Engineering, Finance, Product, and GTM to maximize utilization, manage vendor performance and risk, improve unit economics, and build the operating cadence and dashboards that keep supply healthy and cost-effective.
This is an operator role (not people management). You’ll drive execution through clear processes, metrics, reporting, vendor coordination, and cross-functional alignment.
Providers We Work WithWe source capacity from neocloud and GPU infrastructure providers, including (examples): HydraHost, Shadeform, Voltage Park, and others.
Key ResponsibilitiesUtilization Optimization & Fleet Operations- Own real-time fleet utilization: identify and resolve idle capacity, inefficiencies, and demand/supply mismatches.
- Define utilization targets and operating policies that balance performance, reliability, and cost.
- Develop policies and processes for lifecycle management of vendor-sourced instances (bring-up, steady state, rebalancing, decommissioning).
- Partner with Engineering to define requirements and prioritize automations for capacity acquisition, scaling, rebalancing, failovers, and cost controls.
- Model and monitor GPU unit economics: cost per GPU-hr, marginal cost, blended vendor rates, and cost leakage.
- Partner with Finance & Product to align customer pricing with underlying vendor economics.
- Deliver monthly/quarterly reporting on supply-side cost trends and margin performance, including key drivers and recommended actions.
- Recommend improvements to pricing, contract mix, vendor allocation, and operational policies to expand gross margin.
- Build and maintain forecasting models to predict demand, burst behavior, seasonality, and reserve requirements.
- Determine the optimal mix of contract types (on-demand, committed use, short-term) to maximize flexibility and margin.
- Maintain capacity buffers and contingency plans to protect against vendor outages, degraded performance, or sudden demand spikes.
- Source, evaluate, and manage relationships with neocloud and GPU infrastructure providers.
- Negotiate pricing, SLAs, commitments, contractual flexibility, and scaling terms.
- Create and maintain vendor scorecards (pricing, reliability, latency, responsiveness, and fit).
- Identify emerging vendors, negotiate trial capacity, and assess cost–performance tradeoffs.
- Develop a multi-vendor redundancy strategy to minimize single-provider risk.
- Stand up the core dashboards and operating cadence to monitor and manage (examples):
- per GPU family utilization
- utilization by contract type
- idle capacity
- blended cost per GPU hour
- vendor latency / performance
- error/outage risk indicators
- Help define a practical tool stack for capacity planning and financial analysis. Examples may include:
- Spreadsheets: Excel / Google Sheets
- Data & querying: SQL; data warehouses (e.g., Databricks/BigQuery)
- BI / dashboards: Looker, Tableau, Metabase, Grafana (or equivalents)
- Planning / FP&A platforms
- Work management & documentation: ClickUp/Linear, Notion, Google Docs (or equivalents)
- Serve as the primary operational point of contact across vendors and internal teams for supply-side performance, risk, and escalations.
- Support Sales/GTM with capacity availability and supply risk inputs for large customer deals.
- Advise leadership on supply-side risks, mitigations, and operational opportunities.
- 5+ years in capacity operations, infrastructure operations, technical operations, cloud supply/vendor ops, or a closely related role.
- Demonstrated experience managing external infrastructure vendors (performance management, SLAs, commercial terms, escalation paths).
- Strong analytical skills and comfort with unit economics (cost drivers, margin, pricing inputs, forecasting).
- Experience building operating cadences and dashboards that drive action (not just reporting).
- Clear communicator who can align Engineering, Finance, Product, and GTM around priorities and tradeoffs.
- Prior experience with GPU/compute infrastructure markets, neocloud providers, or large-scale cloud procurement.
- Familiarity with SRE/infra concepts (availability, incident response, capacity buffers) and performance metrics (latency, error rates).
- Experience improving gross margin through contract mix optimization and vendor allocation strategies.
You’ll be the first person dedicated to supply-side operations and economics—setting the baseline metrics, processes, and vendor playbook that scale the business as demand grows.
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What We Do
Parasail is the first AI Deployment Network built for the new era of open and scalable AI. We connect teams to the world’s largest pool of on-demand GPU compute—giving AI builders fast, flexible, and cost-efficient infrastructure to deploy and scale models without contracts, quotas, or cloud complexity. From real-time inference to massive batch jobs, Parasail intelligently matches workloads across a global GPU network, optimizing for performance, price, and geography. No DevOps burden, no vendor lock-in—just plug-and-play access to high-performance infrastructure that works with the latest open-source models and evolving AI stacks. Companies like Weights & Biases, Elicit, Rasa, Everpilot, and Oumi are already building faster and saving up to 30x on costs with Parasail. The future of AI deployment isn’t a single cloud. It’s a global compute network. Parasail is making that future a reality. 🔗 www.parasail.io


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