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Inferact

Open-source LLM inference engine with scalability

Go-to-Market Engineer

Sales OperationsConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • 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 customer relationship management system, including account and opportunity data models, pipeline stages, required fields, routing, process hygiene, and reporting.
  • Ability to work with data, application programming interfaces, integrations, enrichment sources, automation tools, and lightweight scripting to create usable workflows from fragmented commercial information.
  • Understanding of early-stage sales operations, including ideal customer profile definition, prospect research, pipeline management, handoffs, follow-up, and distinguishing useful processes from unnecessary ones.
  • Ability to identify and build high-leverage operating systems from loosely defined problems without waiting for detailed requirements.
  • 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 technical and non-technical stakeholders.

Responsibilities

  • Build the commercial operating system for Inferact, including core infrastructure such as customer relationship management structure, account intelligence, standardized workflows, and repeatable operating processes.
  • Turn fragmented information into systems that make the commercial team faster, more focused, and more effective in partnership with commercial leadership.
  • Create a clean commercial source of truth, help define the sales process, analyze ecosystem and community data to identify high-value prospects and warm paths, and build workflows and automation to support targeted selling.
  • Evolve the commercial system toward scalable prospecting, reporting, and commercial execution as the ideal customer profile becomes clearer, while avoiding unnecessary process.
  • As the sales team grows, help define representative onboarding and training and support sales compensation planning; these broader revenue operations needs are expected from 2027 at the earliest.

Desired Qualifications

  • Experience building go-to-market infrastructure from zero before a company had a mature customer relationship management system, documented ideal customer profile, or standardized sales process.
  • Experience analyzing proprietary or community data sources to identify high-value accounts, warm paths, customer signals, or technically relevant prospects.
  • Experience with artificial-intelligence-native or modern go-to-market workflows, including research automation, enrichment, account intelligence, workflow orchestration, and personalized outbound support.
  • Experience supporting developer tools, artificial intelligence infrastructure, open-source software, cloud platforms, or another highly technical business-to-business product.
  • Comfort combining hands-on go-to-market engineering with revenue operations judgment; experience defining representative onboarding and training or supporting sales compensation plans is a plus for the role's longer-term scope.
  • Experience building a customer relationship management system and commercial operating cadence from scratch for an early-stage startup.
  • Experience creating account research, enrichment, warm-introduction mapping, or prospect-prioritization systems that materially improved seller focus.
  • Experience automating repetitive go-to-market workflows while preserving high-quality human judgment for strategic accounts.
  • Experience working with open-source communities or product-usage data as a source of commercial intelligence.
  • Experience building internal go-to-market tools, dashboards, agents, or data pipelines that became core infrastructure for a commercial team.

About the Company

Inferact

Open-source LLM inference engine with scalability

Inferact builds AI inference infrastructure centered on vLLM, an open-source large language model inference engine. It offers a managed inference service for enterprises with serverless deployment, observability, troubleshooting, disaster recovery, and multi-tenant Kubernetes scaling. vLLM uses PagedAttention to optimize GPU memory, lowering costs and latency while preserving model quality, and Inferact supports new architectures and hardware under vendor-neutral governance with PyTorch Foundation. The goal is to commoditize AI inference and deliver a production-ready operating layer for the AI stack.

Company size
11-50
Company stage
Seed
Total funding
$150M
Headquarters
San Francisco, CA
Founded
2025

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