Principal Software Engineer

ABOUT ENDGAME 🌎 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. HOW WE BUILD 🛠️ 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. WHAT YOU'LL DO 🚀 - 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.

• Ship the frontend features, tRPC routes, and React components that customers interact with daily — from admin dashboards to the core product UI.
• Design and harden the public API layer: authentication, Redis-backed rate limiting, quota enforcement, and the observability to know when something goes wrong.
• 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.
• Translate ambiguous product goals into concrete engineering scope, then ship it.

• Own end-to-end quality on the surfaces you ship: performance, reliability, security, observability. AI raises the floor, your taste raises the ceiling. WHAT WE'RE LOOKING FOR 🏅 - Deep understanding of the TypeScript and JavaScript ecosystem.

• Familiarity with Python.
• Experience designing and implementing LLM and agent tool surfaces, including the tools themselves and the context management around them.
• Experience with frontier AI models in production in cloud environments.
• Experience developing APIs with a real focus on observability and authentication.
• Strong product instincts.

• 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.

• Bonus: prior experience with revenue-data systems (Salesforce, CRMs, sales tooling) or developer-platform infrastructure (SDKs, APIs, agent tooling). BENEFITS 🏆 - Competitive compensation and equity - 401k, health, dental, and vision insurance - Flexible time off - Paid parental leave - Education stipend The qualifications listed in our job descriptions are meant as guidelines, not strict requirements.

• Build a demo integration that syncs Salesforce Opportunity data into a graph database (e.g., Neo4j) and exposes a simple API that returns a “deal context” object; host the code on GitHub with a README that explains the GTM problem you solved, performance metrics (e.g., 10× faster query), and any async processing (Kafka, AWS Lambda) you used—this directly mirrors Endgame’s core product.
• In your résumé and interview, quantify past work that combined GTM strategy with engineering, such as “Reduced sales‑cycle data latency from 48 h to 2 h for a $200M pipeline by redesigning the Salesforce‑to‑data‑warehouse ETL using Bulk API v2 and Airflow.” Endgame will look for impact at scale.
• Prepare a 2‑page architecture diagram (draw.io or Lucidchart) that shows how you would extend Endgame’s context graph to ingest multi‑channel touchpoints (calls, emails, Slack) while preserving ACID guarantees; walk the interviewers through trade‑offs (eventual consistency vs. real‑time) and the tooling you’d pick (Kafka Streams, dbt, GraphQL).
• Highlight remote‑first collaboration: list the specific async tools you master (GitHub PR reviews with code‑owners, Notion docs, Linear for issue tracking, Slack huddles) and cite a concrete example where you led a cross‑timezone design review that shipped a production feature within a sprint. Endgame values self‑directed, distributed teamwork.
• When discussing compensation, research recent Series B remote tech salaries (e.g., $220‑$260k base for Principal Engineers) and factor in Endgame’s equity pool; ask for a “total‑comp” package that includes a signing bonus, a clear vesting schedule, and a remote‑work stipend (home office, coworking space) to align with their startup growth stage.