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HackerRank is seeking a Senior Backend Engineer to drive technical direction and lead delivery of high-impact, platform-level initiatives. You will own the architecture and evolution of core backend services that power the platform used by millions of developers daily.
Key responsibilities include architecting and designing complex backend systems and services at scale; defining and driving technical strategy for your domain with authority over system design and technology choices; owning end-to-end reliability and performance of critical services through SLOs and incident response practices; designing scalable API frameworks and data models that serve as foundations for multiple product teams; leading cross-functional technical initiatives across frontend, infrastructure, product, and design teams; identifying and driving large-scale refactoring efforts to tackle tech debt; mentoring engineers through design and code reviews; and contributing to engineering-wide standards and tooling.
You bring 3-6 years of experience building and operating production backend systems at scale. You are expert in at least one modern backend language (Python, Ruby, Go, Java, Node.js) with strong full-stack fundamentals. You have proven ability to design distributed systems with meaningful architectural decisions around service decomposition, data consistency, fault tolerance, and observability. Deep expertise with relational databases (PostgreSQL, MySQL) and NoSQL stores is required, including schema design, query optimization, and data modeling for high-throughput workloads. You understand caching strategies (Redis/Memcached), asynchronous messaging (Kafka/RabbitMQ), and event-driven architectures. Hands-on experience with containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure-as-code is essential. You have a track record of leading technical projects from ambiguous problem statements through production delivery.
A significant differentiator is AI fluency: deep, hands-on proficiency with AI-powered development tools (GitHub Copilot, Cursor, Claude Code); strong working knowledge of LLMs and agentic AI systems; proven ability to leverage AI across the full software development lifecycle; solid understanding of AI/ML fundamentals including transformer architectures, embedding models, and RAG patterns; ability to evaluate and recommend AI tooling and integration patterns; and active engagement with AI research and tooling developments.
Ideal candidates also have experience designing systems serving millions of concurrent users with strict latency and availability requirements; deep expertise in system design patterns (Microservices, CQRS, Event Sourcing, Domain-Driven Design); significant cloud platform experience (AWS, GCP, Azure); and experience building platform-level APIs and SDKs.
