Senior Backend Engineer

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.

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.

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 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.

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