We're looking for a Senior Backend Engineer to own core infrastructure that powers our platform - from the pipelines that move and process data at scale, to the systems that keep our engineering org shipping fast and reliably. This is a technical leadership role: you'll set architecture direction, raise the bar on engineering practices, and mentor other engineers, while staying deeply hands-on.
You'll operate in an organization that expects AI-native ways of working. Using tools like Claude, Cursor, Hermes or LangGraphor isn't a bonus here - it's the baseline for how we build, and we expect you to help the rest of the team level up on it too.
Nimble is the real-time web search platform built for enterprise accuracy, completeness, and trust. We run Web Search Agents that actively navigate live websites using real browsers and reasoning, turning the public web into governed, decision-grade data for AI systems and high-stakes business use.
Unlike index-based “AI search” tools or brittle legacy scraping, Nimble makes the live web queryable on demand, delivering structured outputs that teams can verify and rely on. Our platform powers use cases where correctness matters: financial due diligence, real-time pricing and promotions, market intelligence, and AI systems that depend on fresh, complete data.
Trusted by leading enterprises like Home Depot, Uber, and Coca-Cola and backed by top-tier investors, Nimble sits at the intersection of AI, automation, and real-time web intelligence.
As demand accelerates across AI, LLMs, and data-driven decisioning, we’re scaling quickly and looking for high-energy, driven teammates who thrive in fast-moving environments and want to help define a new category.
Why join Nimble?
Work on a deeply technical platform powering real-time AI and enterprise decisions
Help define the future of Web Search Agents and live web intelligence
Build alongside a sharp, mission-driven team that moves fast, ships often, and takes ownership
עיקרי התפקיד
Own core backend infrastructure - design and build scalable, reliable Node.js/TypeScript/Python/Go services that other teams and systems depend on.
Build and scale data pipelines - architect the infrastructure that processes and moves large volumes of data reliably, efficiently, and at scale.
Elevate test & validation infrastructure - build the automation, tooling, and CI/CD systems that let engineering ship fast without breaking things, and that make quality and reliability measurable.
Set technical direction - make architecture decisions with company-wide impact, drive design reviews, and establish engineering standards and best practices.
Mentor and multiply - level up other engineers technically, and help shape a fast, high-ownership engineering culture as the team grows.
Lead with AI-native workflows - use AI-assisted development tools daily to move faster without sacrificing architectural quality, and champion their adoption across the team.
דרישות
8+ years of backend software engineering experience, including end-to-end ownership of production systems at scale.
Deep expertise in Node.js and TypeScript, with strong software architecture skills for building modular, distributed systems.
Strong cloud and infrastructure experience (AWS, Kubernetes, Docker), including CI/CD, observability, reliability, and production operations.
Experience building and scaling data-intensive systems, including high-throughput data pipelines, distributed APIs, data modeling (SQL & NoSQL), and messaging platforms such as Kafka or Spark.
Experience building developer infrastructure, including internal tooling, test automation, validation frameworks, or agent-facing infrastructure (e.g., MCP servers, AI/LLM tools and APIs).
AI-native engineering mindset, with daily expert use of AI-assisted development tools (Claude Code, Cursor, Copilot, or similar) to significantly improve engineering velocity while maintaining quality.
Technical leadership experience, including mentoring engineers, driving architecture decisions, and raising engineering standards across a team.
Experience working in fast-paced startup or scale-up environments, delivering for customers under short SLAs.