Fast Facts
Join HackerRank as a Senior Backend Engineer to drive the architecture and evolution of critical backend systems while mentoring engineers and delivering high-impact initiatives.
Responsibilities: Architect and lead the implementation of complex backend systems, define technical strategy, own end-to-end service performance, and mentor engineers.
Skills: Expertise in modern backend programming languages, distributed systems design, relational and NoSQL databases, caching strategies, and containerization technologies.
Qualifications: 3-6 years of experience in backend systems, strong understanding of AI tools, and experience with high-throughput databases and cloud platforms.
Location: Hybrid in Santa Clara, CA
Compensation: Not provided by employer. Typical compensation ranges for this position are between $140,000 - $180,000.
About the role
Every day, millions of developers use HackerRank to prove their skills. We're looking for a Senior Backend Software Development Engineer who can drive the technical direction of critical backend systems and lead the delivery of high-impact, platform-level initiatives. You will own the architecture and evolution of core backend services, mentor engineers across teams, and be a key technical decision-maker ensuring our platform remains fast, reliable, and scalable as we grow our global user base.
What you’ll do
- 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.
- Design scalable API frameworks and data models that serve as foundations for multiple product teams and external integrations.
- Lead cross-functional technical initiatives spanning multiple teams, coordinating with frontend, infrastructure, product, and design stakeholders.
- Identify and drive large-scale refactoring efforts, tackling tech debt and evolving legacy systems into modern, maintainable architectures.
- Mentor and grow engineers on the team through design reviews, code reviews, and hands-on technical guidance.
- Contribute to engineering-wide standards, tooling, and processes that raise the bar for code quality and developer productivity.
Who you are
- Senior backend engineer with 3-6 years of experience building and operating production backend systems at scale.
- Expert in at least one modern backend programming language (e.g., Python, Ruby, Go, Java, or Node.js) with strong fundamentals across the stack.
- Proven ability to design and build distributed systems — you've made meaningful architectural decisions around service decomposition, data consistency, fault tolerance, and observability.
- Deep expertise with relational databases (PostgreSQL, MySQL) and NoSQL stores, including schema design, query optimization, and data modeling for high-throughput workloads.
- 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 ambiguous problem statements through to production delivery.
AI fluency
- Deep, hands-on proficiency with AI-powered development tools (e.g., GitHub Copilot, Cursor, Claude Code) — you don't just use them, you've developed workflows and best practices around them that you can teach others.
- Strong working knowledge of LLMs and agentic AI systems — you understand model capabilities, limitations, context management, tool use, and can reason about when and how to integrate AI into backend systems.
- Proven ability to leverage AI across the full software development lifecycle: architecture exploration, implementation, code review, test generation, documentation, incident analysis, and technical writing.
- 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 for your team and domain — including cost, latency, reliability, and security considerations.
- You actively follow developments in AI research and tooling, can separate hype from real engineering value, and drive adoption of AI-augmented practices within your team.
Even better if you have
- Experience designing and operating systems serving millions of concurrent users with strict latency and availability requirements.
- Deep expertise in system design patterns such as Microservices, CQRS, Event Sourcing, or Domain-Driven Design, with real-world application.
- Significant experience with cloud platforms (AWS, GCP, or Azure), including serverless architectures, managed services, and cost optimization.
- Experience building platform-level APIs, SDKs, or developer tools consumed by internal or external engineering teams.
- A history of driving engineering culture improvements — whether through RFC processes, architecture review boards, or engineering blog contributions.
You will thrive in this role if
- You think beyond the immediate task and consider the long-term health, extensibility, and operational cost of the systems you build.
- You take ownership not just of your own code, but of the overall quality and direction of the systems your team delivers.
- You are energized by ambiguity — you can take a loosely defined problem, structure it, and drive it to a well-engineered solution.
- You lead by influence, earning trust through strong technical judgment and a collaborative, ego-free approach.
- You genuinely enjoy making other engineers better through mentorship, knowledge sharing, and raising the engineering bar.
