Senior Backend Engineer
$150k - $172k • Remote • Hybrid in Santa Clara, CA
Posted 4mo ago
About the job
HackerRank is seeking a Senior Backend Software Development Engineer to drive the technical direction of critical backend systems and lead high-impact, platform-level initiatives. This role involves owning the architecture and evolution of core backend services, mentoring engineers, and making key technical decisions to ensure the platform remains fast, reliable, and scalable for a growing global user base. The ideal candidate will contribute to the company's mission of helping businesses hire and upskill developers based on skills, adapting to the evolving landscape where humans and AI build together.
Responsibilities
- Architect, design, and lead the implementation of complex backend systems and services.
- Define and drive technical strategy for your domain, including system design and technology choices.
- Own the end-to-end reliability and performance of critical backend services.
- Design scalable API frameworks and data models.
- Lead cross-functional technical initiatives spanning multiple teams.
- Identify and drive large-scale refactoring efforts and tackle tech debt.
- Mentor and grow engineers through design and code reviews.
- Contribute to engineering-wide standards, tooling, and processes.
Requirements
- 3-6 years of experience building and operating production backend systems at scale.
- Expertise in at least one modern backend programming language (e.g., Python, Ruby, Go, Java, or Node.js).
- Proven ability to design and build distributed systems.
- Deep expertise with relational databases (PostgreSQL, MySQL) and NoSQL stores.
- Strong understanding of 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 practices.
- Track record of leading technical projects from problem statement to production delivery.
- Deep, hands-on proficiency with AI-powered development tools (e.g., 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: transformer architectures, embedding models, inference optimization, RAG patterns, fine-tuning vs. prompt engineering trade-offs, and evaluation methodologies.
- Ability to evaluate and make technical recommendations on AI tooling, APIs, and integration patterns.
- Actively follow developments in AI research and tooling.