Role Description We are looking for a Senior Full-Stack Engineer to design, build, and ship features end-to-end across one of our core product teams — from the interface a user touches, through the API, down to the data. You own meaningful parts of the product front to back: - Shape the approach with your team. - Build both the UI and the services behind it. - Test them and run them in production. This is a hands-on role: most of your day is spent writing, reviewing, and debugging real code across the stack, with the autonomy to make sound technical decisions and the judgment to know which ones to raise. You care about more than making it work. You think about: - Edge cases - Failure modes - Performance — both on the server and as the user perceives it - Accessibility - The engineers who'll read your code next You collaborate closely with product managers, QA, and fellow engineers to turn ambiguous goals into reliable software, and you push back early when requirements don't add up. You bring an AI-first working style — using AI tooling daily to move faster across design, coding, and review — with the judgment to catch where its output falls short. This is not a role for someone who lives on only one side of the stack. We need an engineer who's genuinely comfortable building and owning a feature from the component to the database, takes it from ambiguous intent to shipped, reliable software, and raises the bar for the team around them. Qualifications - 5+ years of professional software engineering experience building and operating production systems, working across both frontend and backend. - Strong fluency in JavaScript/TypeScript and Python; comfortable owning non-trivial code in both. - Production experience with a modern framework (React, Vue, or similar) in TypeScript. - Hands-on experience building services on AWS — using core compute, data, and identity services. - Comfortable with modern CI/CD and Git workflows. - Strong production instincts: writes testable code, handles failure deliberately, and can debug and profile a live system. - Reads and works within an existing architecture. - AI-first working style: hands-on daily use of AI tooling with the judgment to verify its output. - Senior judgment and autonomy: takes ambiguous requirements to ship software with minimal hand-holding. - Advanced English; comfortable in a fully remote, distributed team. Requirements - Frontend depth: working grasp of responsive layout, accessibility, and browser performance. - Backend depth: building services and APIs (REST/GraphQL or event-driven) with solid data modeling across relational and non-relational stores. - Experience integrating with multiple third-party platforms in production. - Exposure to Infrastructure as Code (Terraform, CloudFormation/CDK, or Pulumi). - Experience working in multi-tenant or enterprise-facing products with real security and data-residency constraints. - Familiarity with observability tooling (Datadog, Grafana, Sentry, or similar). - Experience mentoring engineers or leading the implementation of a sizable feature. Benefits - 💵 Monthly USD Service Fee - 🌴 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays - 🐣 Caregiver Time Off - 💻 A dynamic remote work culture. You can work from anywhere! - 🚀 An entrepreneurial environment.

• Develop, implement, and deploy scalable, efficient, and reusable front-end and back-end solutions. • Build performant front-end applications that consume and present large volumes of data. • Write clean, maintainable, and well-documented code. • Refactor existing services for a sustainable future. • Collaborate with fellow engineers, product managers, and stakeholders to ensure we're building the right features, in the right way, to advance the platform. • Improve application performance through caching, optimization, and efficient data delivery strategies.

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

• Design and champion internal Quality Programmes: Drive engineering-wide process changes and ensure pods adopt new reliability standards without friction. You will operate with a product-owner mindset to define and evangelize the internal reliability roadmap. • Define and enforce hard metrics: Measure and establish hard quality telemetry (e.g., DORA metrics, bug-to-deploy ratios, SLIs/SLOs) to create a quantifiable baseline for platform reliability. • Architect Shift-Left Pipeline Gates: Weave automated Performance, Security, and Accessibility checks directly into the CI/CD pipeline at the PR level in tight partnership with Eng Core. • Build Real-World Load Testing: Shift load and performance testing left for every customer onboarding, validating real-world assumptions. • Engineer Synthetic Data & Production Canaries: Build the architecture for safe synthetic data injection to unblock heavy load-testing and live-production canaries, strictly isolating test data from authentic user telemetry. • Leverage Generative AI Tooling: Actively utilize AI assistants (e.g., Gemini, Claude, Cursor, Codex) to accelerate the development of testing frameworks, automate infrastructure code, and design advanced testing architectures. • Drive Tooling Consolidation: Lead the technical migration away from expensive, legacy testing infrastructure to a unified, AI-supported automation stack. • Help define and maintain development practices: Enable fast iteration while ensuring quality, including writing tests and documenting key implementations.