Senior Backend Engineer

About this role

ABOUT THE ROLE This is a high-impact individual contributor role on the backend engineering team of an early-stage AI-native platform for cloud architecture planning. You will design and build the intelligent systems that power observability, architecture modeling, and AI-driven recommendation engines, sitting at the intersection of distributed systems, data pipelines, and ML infrastructure. WHAT YOU'LL DO - Design and build scalable backend systems powering observability, architecture modeling, and recommendation engines using data pipelines, microservices, and system modeling techniques.

- Collaborate with AI engineers to embed LLM-based and multi-agent intelligence within the platform, enabling rich recommendations and generative planning capabilities. - Contribute to core architecture capabilities by identifying patterns, building services that reflect architecture decisions, and ensuring actionable visibility for users. - Implement monitoring, fault-tolerant workflows, and observability layers for mission-critical services.

- Work cross-functionally with product managers, AI researchers, and technical leadership to translate requirements into robust platform capabilities. - Share learnings and mentor teammates to strengthen overall engineering culture. WHAT WE'RE LOOKING FOR - 4+ years of backend engineering experience at high-growth startups or technology companies, building production-grade systems. - Proven track record designing scalable, distributed systems and microservices architectures in production environments.

- Expertise in Go or Python with a commitment to clean, idiomatic, maintainable code. - Experience building data pipelines, observability systems, and monitoring infrastructure for production services. - Hands-on experience with DevOps tooling, infrastructure-as-code, and cloud-native technologies. - Experience integrating or working with LLM-based systems, AI workflows, or multi-agent architectures. - Track record of building 0-to-1 systems or products from inception in startup or early-stage environments.

- Demonstrated skill in performance tuning, debugging complex systems, and technical architecture design. - Practical experience with fault-tolerant workflow design and resilience patterns in mission-critical services. - Comfort and proficiency with AI-assisted development tools. - Strong computer science fundamentals; graduate-level education is a plus. - Domain experience in cloud architecture, infrastructure optimization, or technology stack modernization is a bonus.