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HumanSignal

AI Engineer (GTM)

Sorry, this job was removed at 07:27 p.m. (PST) on Monday, Jun 01, 2026
Remote
Hiring Remotely in USA
Remote
Hiring Remotely in USA

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About HumanSignal

Real-world data is the competitive edge in AI.

HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery.

We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide.

We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out.

If you want to do work that materially shapes how the next generation of AI products gets built, we'd love to talk.

About the Role

We’re looking for an ambitious AI Engineer to transform how our go-to-market team operates. San Francisco, Austin, or Lisbon are preferred locations where you can collaborate with team members, but the position is remote or hybrid. 

As the founding GTM engineer, you will architect and build the AI-powered systems that power our entire GTM motion, owning the technology stack, partnering with stakeholders to define the workflows, deploying AI agents and apps, and continuously improving how the company acquires, activates, and grows customers.

This is a highly hands-on role for someone who enjoys shipping systems, experimenting rapidly, and solving messy real-world problems with software.

Why This Role Matters

This role is a force multiplier for the entire company. You’ll build the infrastructure that allows the GTM team to move faster, learn faster, and scale without proportional headcount. You’ll help us:

  • Turn GTM from a set of tools into a cohesive, intelligent system
  • Scale workflows without scaling headcount
  • Improve signal quality and timing for marketing and sales
  • Increase learning velocity across the entire funnel
  • Shape how an open-source, bottom-up product grows into enterprise adoption
What You’ll DoBuild & Automate the foundational GTM AI stack
  • Design, build, and maintain AI systems across marketing, PLG, sales, and post-signup activation
  • Own integrations and workflows across tools like CRM, marketing automation, product analytics, data warehouse, enrichment tools, and internal services
  • Build internal tools and lightweight services that accelerate GTM teams
  • Replace manual workflows with scalable, automated systems
AI-Powered Systems & Agents

Design and deploy AI-driven workflows and agents that augment GTM teams.

Examples include:

  • Lead qualification, inbound lead routing, and enrichment
  • Personalized lifecycle marketing and outbound messaging
  • Sales assist tools for deal intelligence and account research
  • Automated account insights, pipeline analysis, and deal lifecycle management
  • User onboarding, activation, and expansion signals

You’ll continuously improve these systems using real performance data and feedback loops.

Growth: PLG + Sales-Assisted Motion
  • Support a hybrid GTM model where open-source and self-serve users graduate into paid, sales-assisted customers
  • Partner with Data & Growth to build systems that surface product signals (usage, intent, readiness) to marketing and sales teams at the right time
  • Partner closely with Product & Marketing to turn usage insights into GTM leverage
Experimentation & Learning

Build the infrastructure that allows the GTM team to learn quickly and iterate with confidence.

  • Design and run experiments across acquisition, activation, conversion, and expansion
  • Build experimentation frameworks (feature flags, A/B testing, measurement systems)
  • Instrument systems to capture reliable data and insights
  • Rapidly iterate based on results, not assumptions
Feedback Loops & Continuous Improvement

Create tight feedback loops between users, product signals, and GTM actions.

  • Partner with head of , accessible, and actionable across teams
  • Turn qualitative and quantitative insights into system improvements
  • Continuously optimize workflows, models, and automation based on real outcomes
What We’re Looking ForCore Skills

This is fundamentally an engineering role, not traditional GTM operations. We’re looking for someone who enjoys building systems, not managing tools.

  • Strong engineering background (software, data, or growth engineering)
  • Comfortable shipping production code (APIs, services, scripts, internal tools)
  • Experience working with data pipelines, analytics, and experimentation frameworks
  • Hands-on experience with AI/LLMs, prompt engineering, or agent-based systems
Collaboration & Ownership
  • Ability to work cross-functionally with Product, Engineering, Marketing and Sales
  • Comfortable operating with ambiguity and defining the problem as you go
  • Strong communicator who can translate between technical and GTM stakeholders
Nice to Have
  • Experience with open-source or developer-focused products
  • Familiarity with CRM systems (e.g., Salesforce, HubSpot), CDPs, and marketing automation
  • Experience building internal tools for sales or marketing teams
  • Prior work in B2B SaaS, data, or AI-first companies

HQ

HumanSignal San Francisco, California, USA Office

San Francisco, California, United States, 94103

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

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