Senior Backend Engineer

Join HackerRank, a platform used by millions of developers to prove their skills. As a Senior Backend Engineer, you will drive the technical direction of critical backend systems, own the architecture and evolution of core backend services, and mentor engineers across teams. You will also define and drive technical strategy, own the end-to-end reliability and performance of critical backend services, and lead cross-functional technical initiatives.

• Architect, design, and lead the implementation of complex backend systems and services that power core product experiences at scale.
• Define and drive technical strategy for your domain, making key decisions on system design, technology choices, and long-term architectural direction.
• Own the end-to-end reliability and performance of critical backend services, establishing SLOs, monitoring, and incident response best practices.

• Feel energised by ambiguity and be able to structure loosely defined problems and drive them to well-engineered solutions
• Track record of leading technical projects from ambiguous problem statements through to production delivery
• Ability to evaluate and make technical recommendations on AI tooling, APIs, and integration patterns for your team and domain, including cost, latency, reliability, and security considerations
• Expertise in at least one modern backend programming language, such as Python, Ruby, Go, Java, or Node.js, with strong fundamentals across the stack
• Actively follow developments in AI research and tooling, distinguish hype from engineering value, and drive adoption of AI-augmented practices within your team
• Strong understanding of caching strategies (Redis/Memcached), asynchronous messaging (Kafka/RabbitMQ), and event-driven architectures
• Proven ability to use AI across the software development lifecycle, including architecture exploration, implementation, code review, test generation, documentation, incident analysis, and technical writing
• Solid understanding of AI/ML fundamentals, including transformer architectures, embedding models, inference optimisation, RAG patterns, fine-tuning and prompt-engineering trade-offs, and evaluation methodologies
• Hands-on experience with containerisation (Docker/Kubernetes), CI/CD pipelines, and infrastructure-as-code practices
• Think beyond the immediate task and consider the long-term health, extensibility, and operational cost of the systems you build
• Deep expertise with relational databases (PostgreSQL, MySQL) and NoSQL stores, including schema design, query optimisation, and data modelling for high-throughput workloads
• 3–6 years of experience building and operating production backend systems at scale
• Deep, hands-on proficiency with AI-powered development tools (e.g., GitHub Copilot, Cursor, Claude Code), including developing workflows and best practices that you can teach others
• Strong working knowledge of LLMs and agentic AI systems, including model capabilities and limitations, context management, tool use, and when and how to integrate AI into backend systems
• Genuinely enjoy helping other engineers improve through mentorship, knowledge sharing, and raising the engineering bar
• Proven ability to design and build distributed systems, including making architectural decisions around service decomposition, data consistency, fault tolerance, and observability
• Lead by influence, earning trust through strong technical judgment and a collaborative, ego-free approach
• Take ownership of the overall quality and direction of the systems your team delivers, not just your own code
• Significant experience with cloud platforms (AWS, GCP, or Azure), including serverless architectures, managed services, and cost optimisation
• Experience building platform-level APIs, SDKs, or developer tools consumed by internal or external engineering teams
• Deep expertise in system design patterns such as Microservices, CQRS, Event Sourcing, or Domain-Driven Design, with real-world application
• Experience designing and operating systems serving millions of concurrent users with strict latency and availability requirements
• A history of driving engineering culture improvements, whether through RFC processes, architecture review boards, or engineering blog contributions