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Unstructured TechnologiesUT

GTM Engineer, Operations

Unstructured.io is a company that specializes in transforming unstructured data from various formats into LLM-ready data, enabling enterprises to leverage their internal data for AI applications.

Unstructured Technologies

Employee count: 51-200

Salary: 120k-150k USD

United States only

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About Unstructured

Unstructured is redefining how organizations unlock the value of unstructured data (PDFs, HTML, Word docs, emails, and more) for AI/ML pipelines. Our open-source library has been downloaded over 70 million times and is trusted by more than 65,000 companies, including nearly half the Fortune 500. We're backed by leading investors like Menlo Ventures, Databricks Ventures, Bain Capital, and IBM Ventures.

We're building the definitive stack for file transformation and data orchestration, enabling enterprises to connect any data to any model with speed, precision, and scale.

What You'll Do

  • Own and evolve HubSpot CRM architecture: deal stages, pipeline configuration, property management, record automation, and data hygiene at scale.
  • Build and maintain workflow automation across the full GTM funnel: lead routing, lifecycle stage progression, assignment rules, and sales stage enforcement.

  • Design and operationalize the Marketing -> BDR -> AE lead -> Solutions implementation handoff, including routing logic, SLAs, and feedback loops.

  • Own deal desk, CPQ, and quote-to-cash processes, working with sales and BizOps to ensure clean handoffs from signed contract to provisioning to payment made.

  • Ship custom integrations and tools using AI-assisted development (Claude Code, etc.) that solve real operational problems and run in production.

  • Support GTM team onboarding and enablement: build onboarding workflows, maintain playbook distribution, and ensure new hires are productive in the stack quickly.

  • Manage attribution and lead funnel reporting in conjunction with Marketing/Growth to ensure pipeline sources and conversion metrics are accurate.

  • Conduct build vs. buy analysis for new tooling needs. Not everything needs to be custom-engineered; know when to configure, when to integrate, and when to build.

What We're Looking For (Essential Skills)

  • 4+ years in GTM (revenue/marketing/sales) operations or GTM engineering at a B2B SaaS company.
  • Deep HubSpot CRM experience, including workflow automation, custom properties, and pipeline management.

  • Experience building and maintaining workflow automations (HubSpot workflows, n8n, Zapier, or similar).

  • Proficiency with AI-assisted development tools (Claude Code, Codex, Cursor, etc.). Must have shipped a tool, integration, or automation to production that a team actually uses.

  • Experience with lead routing (including Marketing to BDR to AE handoff), deal stage management, and sales process design.

  • Experience with designing system for handoff of accounts from Sales to Solutions for technical implementation

  • Experience with CPQ, billing integrations, or deal desk operations.

  • Experience with owning sales enablement processes, such as a GTM team onboarding processes/automations

  • Ability to run quick build vs. buy analyses: not everything needs to be custom-engineered.

  • A documentation-heavy mindset with a knack for effective change management

Nice-to-Have Skills

  • Familiarity with Clay for data enrichment.
  • Experience at a developer-focused or open-source company.

  • Experience with Enterprise ICPs and complex, multi-stakeholder sales cycles.

Why Unstructured

  • Join a company at the cutting edge of AI + data infrastructure, powering the future of generative AI.
  • Own the systems engineering layer of GTM at a Series B company. Real ownership, not ticket-taking.
  • Work on a team that builds and deploys full-stack apps, AI-powered tools, and custom integrations. You'll ship things that matter.
  • Small team (3 people, 10 functions) = massive scope and direct impact on how the company sells.
  • You're encouraged to experiment with tools. Freedom to build.
  • Competitive compensation, equity, and benefits.

About the job

Apply before

Posted on

Job type

Full Time

Experience level

Mid-level

Salary

Salary: 120k-150k USD

Experience

4 years minimum

Location requirements

Hiring timezones

United States +/- 0 hours

About Unstructured Technologies

Learn more about Unstructured Technologies and their company culture.

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Unstructured addresses a significant challenge many enterprises face: leveraging their vast amounts of unstructured data for use with large language models (LLMs) and other AI applications. Customers often struggle with data in various formats like PDFs, Word documents, PowerPoint presentations, HTML files, images, and more, which are not readily usable by machine learning models. This is where Unstructured steps in, providing solutions to automate the preprocessing of this messy, human-generated data. Our platform transforms raw data into clean, structured formats, making it compatible with LLMs for tasks such as fine-tuning, pre-training, and Retrieval Augmented Generation (RAG).

Our customers need to unlock the potential of their internal data to enhance productivity, drive innovation, and gain actionable intelligence. Unstructured offers open-source libraries and commercial API products designed to simplify and accelerate this data transformation process. We enable organizations to connect their enterprise data, regardless of file type or layout, to LLMs efficiently. This means data scientists and engineers no longer need to spend the majority of their time on the laborious task of data preprocessing, which traditionally involves building custom, brittle pipelines for each data type. By providing robust tools for data ingestion, partitioning, cleaning, and staging, Unstructured empowers businesses to build powerful AI applications based on their own specific, high-quality data, rather than relying solely on generic, pre-trained models. This allows for more accurate, relevant, and secure AI-driven insights and workflows.

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Unstructured Technologies

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