Team Lead Backend Engineer

• Lead the design and development of APIs that expose GTM data to internal and external users.
• Own end-to-end architecture for large-scale data access patterns, optimizing for performance, cost, and reliability.
• Collaborate closely with AI, data, and frontend teams to ensure seamless integrations and clean API contracts.
• Tackle complex problems like versioning, rate-limiting, auth, query complexity, and cache invalidation across a fast-evolving product surface.
• Build internal tooling to improve engineering velocity and observability for our backend systems.
• Drive engineering best practices, code quality, and testing in a fast-paced, high-output environment.
• Mentor engineers and set the technical direction for the team.

• 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
• 5+ years of backend engineering experience, ideally with exposure to high-scale systems.
• Deep experience with modern backend stacks - we use Node.js, ClickHouse and AWS
• Strong understanding of API design principles, query optimization, and distributed systems.
• You’ve worked with large-scale data systems (think TBs of data) and know how to manage performance, cost, and uptime at scale.
• Startup mindset - you move fast, figure things out, and don’t wait to be told what to do.
• Comfortable owning ambiguity - you define the problem, architect the solution, and ship the result.

HockeyStack is building the agent infrastructure for enterprise revenue. We spent five years building the only data architecture that preserves causality across the full revenue stack - every interaction, every signal, in sequence. On top of that foundation, we built Nex-lm, a purpose-built AI engine that compiles natural language into deterministic agent workflows. The result is a platform that can extract the revenue blueprint from a company’s data, encode it into repeatable automations, and execute it across sales, marketing, and customer success - consistently, at scale.

We are not building a dashboard tool with an AI feature. We are building the operating layer that replaces the human bottleneck in enterprise revenue organizations. This is a category being defined right now, and we intend to own it.

We have raised $50M+ from Bessemer Venture Partners, General Catalyst, Y Combinator, and others.

We operate fully in-person in San Francisco. We move fast and we hire people who want to win.

Since launching late 2023, we have grown to 8-figures in ARR, process over 60 TB of revenue data monthly, and we are working with some of the largest B2B companies in the world like Microsoft, Harvey, New Relic, Collibra, etc.