Senior Backend Engineer
HackerRank11 days ago
Responsibilities
- Architect, design, and lead implementation of complex backend systems and services at scale.
- Define technical strategy, system design decisions, technology choices, and long-term architectural direction.
- Own reliability and performance for critical backend services, including SLOs, monitoring, and incident response practices.
- Design scalable API frameworks and data models for product teams and external integrations.
- Lead cross-functional technical initiatives involving frontend, infrastructure, product, and design stakeholders.
- Drive large-scale refactoring and modernization of legacy systems.
- Mentor engineers through design reviews, code reviews, and hands-on technical guidance.
- Contribute to engineering standards, tooling, processes, and developer productivity improvements.
- Lead technical projects from ambiguous problem statements through production delivery.
- Evaluate AI tooling, APIs, and integration patterns based on cost, latency, reliability, and security.
Requirements
- 3–6 years of experience building and operating production backend systems at scale.
- Expertise in at least one modern backend language such as Python, Ruby, Go, Java, or Node.js.
- Experience making architectural decisions involving service decomposition, data consistency, fault tolerance, and observability.
- Deep expertise with relational databases such as PostgreSQL and MySQL and with NoSQL stores, including schema design, query optimization, and data modeling.
- Understanding of caching strategies using Redis or Memcached and asynchronous messaging using Kafka or RabbitMQ.
- Hands-on experience with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code practices.
- Hands-on proficiency with AI development tools such as GitHub Copilot, Cursor, and Claude Code.
- Working knowledge of LLMs and agentic AI systems, including model capabilities, context management, and tool use.
- Understanding of transformer architectures, embedding models, inference optimization, RAG patterns, fine-tuning, prompt engineering, and evaluation methodologies.
- Preferred experience serving millions of concurrent users, designing platform APIs or SDKs, operating cloud systems on AWS, GCP, or Azure, and applying patterns such as CQRS, Event Sourcing, or Domain-Driven Design.
- Preferred experience driving engineering culture improvements through RFC processes, architecture review boards, or engineering blog contributions.
Tech Stack
Apache KafkaAWSAzureDockerGoGoogle Cloud PlatformJavaKubernetesMySQLNode.jsPostgreSQLPythonRabbitMQRedisRuby
Categories
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