AI Engineer
HockeyStackSan Francisco$180k – $220kPosted 19 March 2026
Job Description
AI Engineer
HockeyStack is building the AI system that runs B2B sales and marketing.
We integrate with every tool across the go-to-market stack, combine it with first and third-party data, and build the most complete event-level data foundation in the industry. On top of it, we:
- Mine every won and lost deal to reverse-engineer the patterns that drive revenue, then deploy agents that guide reps through the optimal process deal by deal, in real time.
- Surface what’s really driving pipeline and what isn’t, replacing weeks of manual analysis with answers on demand.
- Learn from every outcome and every rep interaction, getting sharper over time — not just when someone rewrites a prompt.
We’re not wrapping LLMs around prompts and guessing. We’ve built a structured reasoning layer that makes agent execution deterministic and self-improving — something no other player in the market has done.
Y Combinator alum. $26M Series A led by Bessemer Venture Partners. 3× YoY growth. 8-figure ARR. 60+ TB of GTM data processed. We move fast and hire people who are ready to win. This role is based at our San Francisco HQ.
🚀 YOUR MISSION
As an AI Engineer your mission is to harness the power of agentic AI in building the single portal where GTM team members go to grow their business. You’ll push the boundaries of what LLMs can do — designing systems that don’t just respond to prompts but autonomously orchestrate complex sales and marketing workflows, learn from outcomes, and get sharper over time.
🔧 WHAT YOU’LL DO
- Own and continuously improve the backend systems that power all agentic AI features across the platform
- Design, write, and maintain agents responsible for different tasks across a GTM team’s workflows, leveraging the latest agent frameworks
- Develop and maintain backend services in Node.js that power these agents
- Build state-of-the-art context management pipelines and manage thousands of stateful agents.
- Ship fast and often — deploying to production frequently while maintaining high-quality standards
🧬 WHAT WE’RE LOOKING FOR
- Ownership-first mindset — you take initiative, move fast, and figure things out
- Thrive in early-stage, high-urgency environments where speed and impact matter
- Fully committed to working in-person 5 days/week at our SF HQ
- Curious, self-aware, and feedback-driven — you bring energy, not ego
- See this role as a defining chapter — not a stepping stone or side quest
What you bring:
- Hands-on experience building and deploying LLM-powered applications or agentic AI systems in production
- Strong backend engineering experience with Node.js and modern JavaScript/TypeScript
- Experience designing and orchestrating multi-agent systems, including managing agent state, memory, and context across complex workflows
- Familiarity with modern AI frameworks and providers (Braintrust, Cerebras, Langchain or similar)
- Understanding of multi-model architectures — knowing when and how to route tasks across different LLMs for cost, speed, and quality tradeoffs
- A track record of shipping in fast-moving, production environments
✨ WHY JOIN NOW
We’re at an inflection point. The product is proven, the market is massive, and the opportunity is wide open. You’ll be joining a company with real traction, rapid growth, and meaningful backing — where every person still shapes the outcome. This isn’t just a job. It’s a chance to build something category-defining with people who care deeply about doing it right.
As part of our San Francisco, California-based team, the salary range for this role is $180,000- $220,000 USD base pay annually, depending on experience and qualifications.
HockeyStack is proud to be an Equal Opportunity Employer. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other legally protected status. We celebrate diversity and are committed to fostering an inclusive env ... (truncated, view full listing at source)
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