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Inferact, founded by the creators and core maintainers of vLLM, is building the world's AI inference engine. The company sits at the intersection of models and hardware, positioning itself to accelerate AI progress by making inference cheaper and faster.
You'll be the first GTM Engineer, building the commercial operating system from the ground up. This is a hands-on role combining GTM engineering with a secondary RevOps remit. The GTM organization is early enough that core infrastructure—CRM structure, account intelligence, standardized workflows, and repeatable operating processes—are still being defined.
You'll partner closely with commercial leadership to turn fragmented information into systems that make the team faster, more focused, and more effective. Early projects include creating a clean commercial source of truth, helping define the sales process, mining Inferact's unique ecosystem and community data to identify high-value prospects and warm paths, and building workflows and automation that support targeted selling.
As the ICP becomes clearer, you'll evolve the system toward scalable prospecting, reporting, and commercial execution without adding unnecessary process. As the sales team grows, you'll help define rep onboarding and training and support sales compensation planning—broader RevOps needs expected from 2027 at the earliest.
This role requires someone who can take a blank-sheet problem, identify the highest-leverage operating system to build, and ship it without waiting for detailed requirements. You'll work directly with commercial leadership, founders, product, engineering, and external implementation partners.
REQUIREMENTS:
Minimum qualifications:
- Experience building or operating go-to-market systems, revenue operations, sales operations, or GTM engineering workflows in a startup or high-growth technology environment
- Hands-on experience implementing and structuring a CRM, including account and opportunity data models, pipeline stages, required fields, routing, process hygiene, and reporting
- Strong ability to work with data, APIs, integrations, enrichment sources, automation tools, and lightweight scripting to turn fragmented commercial information into usable workflows
- Understanding of how an early-stage sales organization operates, including ICP definition, prospect research, pipeline management, handoffs, follow-up, and the difference between useful process and unnecessary process
- Ability to take a blank-sheet problem, identify the highest-leverage operating system to build, and ship it without waiting for detailed requirements
- Strong communication and collaboration skills with the ability to work directly with commercial leadership, founders, product, engineering, and external implementation partners
- Ability to translate commercial needs into clear system and data requirements and communicate tradeoffs to both technical and non-technical stakeholders
Preferred qualifications:
- Experience building 0-to-1 GTM infrastructure before a company had a mature CRM, documented ICP, or standardized sales process
- Experience mining proprietary or community data sources to identify high-value accounts, warm paths, customer signals, or technically relevant prospects
- Experience with AI-native or modern GTM workflows, including research automation, enrichment, account intelligence, workflow orchestration, and highly personalized outbound support
- Experience supporting developer tools, AI infrastructure, open-source software, cloud platforms, or another highly technical B2B product
- Comfort combining hands-on GTM engineering with RevOps judgment; experience defining rep onboarding and training or supporting sales compensation plans is a plus for the role's longer-term scope
Bonus:
- Built a CRM and commercial operating cadence from scratch for an early-stage startup
- Created account research, enrichment, warm-intro mapping, or prospect prioritization systems that materially improved seller focus
- Automated repetitive GTM workflows while preserving high-quality human judgment for strategic accounts
- Worked with open-source communities or product-usage data as a source of commercial intelligence
- Built internal GTM tools, dashboards, agents, or data pipelines that became core infrastructure for a commercial team
