Senior Backend Engineer II

About this role The mission of the Senior Backend Engineer is to design, build, and operate the backend services powering Keystone AI's platform for carriers and shippers in the U.S. vehicle transportation industry. As part of an agile team, you'll own technical decisions on architecture, APIs, and infrastructure - maintaining production excellence, communicating trade-offs clearly, and mentoring engineers. What you'll work on Keystone AI's backend runs vehicle shipments end to end, with much of the work happening in background and event-driven flows. You'll take on problems like: Architecture and refactoring — reshaping core services and data models as the product grows, and paying down tech debt without stalling delivery. Reliable background processing — making our task and worker pipelines safe under failure so jobs aren't dropped, lost, or double-processed. Resilient partner integrations — keeping outbound integrations reliable under failure, with sensible retries and idempotency. Endpoint and query performance — profiling and optimizing slow endpoints and database queries as data and traffic grow. Why Keystone AI At Keystone AI, we're not just changing the game - we're creating a whole new playing field in the auto transport industry. Keystone AI is the next generation platform that is not only redefining efficiency but is also setting new standards for how vehicles are moved. Our suite of tools, including the Carrier TMS, Shipper TMS, SuperPay, and the groundbreaking Super Loadboard, are designed with one goal in mind: making auto transport as easy as possible. Leverage the latest in industry trends, data, and user-friendly features, empowering carriers, shippers, and brokers to achieve operational excellence. From minimizing paperwork to reducing wasted time and cutting costs, we tackle the challenges of the industry head-on, so you can focus on what you do best. Welcome to Keystone AI, where the future of auto transport is already a reality. Responsibilities The role is organized around three areas of ownership: Individual Contributor Technical Depth Own multiple backend services end-to-end — architecture, REST APIs, databases. Design, build, and debug asynchronous and concurrent systems — task queues, background workers, and event-driven flows — including their failure modes (retries, ordering, idempotency, race conditions). Use AI coding assistants daily (e.g., Cursor, Claude Code) to accelerate design, implementation, tests, and docs — reviewing output critically for correctness and security, and helping set sensible team norms. Own third-party API integrations — implementation, cost control, rate-limiting, and ongoing maintenance. Mentor junior/mid engineers on architecture, patterns, and production readiness. Contribute to backend technical standards and best practices. Operational Ownership Own observability tooling — dashboards, alerting, and SLA tracking for services. Participate in the backend on-call rotation as first responder for production incidents Lead the QA partnership on test strategy. Own subsequent post-launch support; triage customer escalations. Product & Cross-Functional Collaboration Translate product requirements into technical specs and own technical scope. Communicate architectural trade-offs (performance, cost, latency) to stakeholders. Collect Support feedback and iterate on API usability and documentation. Collaborate with Design and Frontend on API contracts and payloads. Candidate Experience You have 7+ years of professional backend experience (10+ preferred), including time at a senior or staff level in a product-driven environment. You are proficient in Python with strong experience in Django and/or FastAPI. You're strong with concurrent and asynchronous Python (asyncio for in-process concurrency; Celery or similar task queues for distributed background work) and can design, implement, and (critically) debug these systems under real production conditions. You've worked on offline-first or unreliable-network sync, including optimistic updates, queue-and-replay, and conflict resolution. AI coding assistants are a daily part of your workflow (scaffolding, refactoring, exploring unfamiliar code, drafting tests and docs), and you review their output critically for correctness, security, and latency, knowing when not to reach for them and helping set sensible team norms. You have hands-on experience with SQL databases like PostgreSQL (schema design, query optimization). You've worked with at least one message broker or streaming platform (e.g., Kafka, RabbitMQ) and understand delivery semantics (ordering, idempotency, retries). You reach for the right data structures and algorithms when they matter for correctness or performance, and you know when not to over-engineer. You have a solid understanding of system design and microservices. You write automated tests as a matter of course — unit, integration, and end-to-end (e.g., pytest, tox, Playwright) — and