Principal Software Engineer

Endgame is the context graph for every GTM agent. We process every call, deal, and playbook into structured knowledge that both humans and AI agents can act on — 140× faster and a fraction of the cost of throwing raw data at an LLM.

Revenue teams at Monte Carlo, BetterUp, Braze, and dozens of other leading companies use Endgame as their source of truth. Instead of context scattered across fifteen disconnected systems, their reps, managers, and CS teams — and the agents working alongside them — all operate from the same structured view of every customer and every deal.

We've raised $47.5M from EQT Ventures, Menlo Ventures, Upfront Ventures, and Unusual Ventures, plus executives from Zoom, Stripe, Notion, and Airtable. We're a team of ~25, mostly engineers, and we build production systems with real architecture — not prototypes.

We're an AI-native engineering team. Agentic coding tools are integral to how we build and ship 15-20 times daily, if not more. We build with Claude Code, Cursor, and Copilot, and we're constantly sharing what works and what doesn't. We move fast, we're not afraid to throw things away, and we keep the bar high because customers depend on us. You'll help push that culture forward.

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  Build and evolve the MCP server and agent tool surfaces that AI clients use to query Endgame's context graph — designing tool schemas, managing context windows, and making sure every tool call returns the right data fast.

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  Ship the frontend features, tRPC routes, and React components that customers interact with daily — from admin dashboards to the core product UI.

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  Design and harden the public API layer: authentication, Redis-backed rate limiting, quota enforcement, and the observability to know when something goes wrong.

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  Wire new data sources into the product by integrating with the context graph and making that data available through both human-facing UI and agent-facing tool surfaces.

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  Translate ambiguous product goals into concrete engineering scope, then ship it. You'll work closely with product, design, and the rest of engineering, and you'll often be the person turning a customer pain point into a novel solution.

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  Own end-to-end quality on the surfaces you ship: performance, reliability, security, observability. AI raises the floor, your taste raises the ceiling.

• Deep understanding of the TypeScript and JavaScript ecosystem. You've built and maintained serious systems in it, not just touched it.

• Familiarity with Python.

• Experience designing and implementing LLM and agent tool surfaces, including the tools themselves and the context management around them.

• Experience developing APIs with a real focus on observability and authentication.

• Strong product instincts. You can take an ambiguous product requirement and translate it into deliverable engineering scope.

• Deep experience with agentic coding tools and modern testing practices. You use AI coding tools daily, have opinions about them, and know when to trust the agent versus reading the diff yourself.

• You default to collaborative action. You write, you share early, you make decisions reversible when you can.

• Bonus: prior experience with revenue-data systems (Salesforce, CRMs, sales tooling) or developer-platform infrastructure (SDKs, APIs, agent tooling).