Overview
We are seeking a skilled and passionate Senior Backend Engineer to join our team, focusing on the design, development, and maintenance of high-performance, scalable microservices. The ideal candidate will have strong expertise in Go (Golang), and a deep understanding of distributed systems architecture.
Core Experience
- 7+ years of professional experience in backend software development, with a significant focus on building and operating microservices in a production environment.
- Proven ability to work with and contribute to large-scale, distributed systems.
- Experience with cloud platforms (AWS, Azure, or GCP) for deployment, monitoring, and scaling.
Process & Tools
- CI/CD: Experience setting up and maintaining automated deployment pipelines
- Observability: Proficiency with monitoring and logging tools
- Source Control: Expertise in Git and collaborative workflows
Architecture & Design
- Familiarity with event-driven architectures and streaming data processing
- Experience with security best practices in API design (e.g., OAuth 2.0, JWT, input validation)
- Knowledge of performance tuning and optimization techniques for both Python and Go applications
Key Responsibilities
- Design, implement, and maintain scalable and reliable backend microservices using Go
- Collaborate with product managers and front-end teams to define API specifications and integration points
- Ensure services are deployed, monitored, and scaled efficiently in a Kubernetes environment
- Participate in code reviews, design discussions, and planning sessions
- Troubleshoot and resolve complex production issues, ensuring high availability and performance
- Drive continuous improvement in development processes, tooling, and infrastructure
Production Microservices Ownership
- Has owned at least 1–2 services end-to-end (design → build → deploy → on-call → incident fixes → scaling)
- Comfortable with service boundaries, APIs, versioning, backward compatibility, SLAs/SLOs
System Design & Architecture
- Can design systems with tradeoffs: latency, throughput, cost, reliability
- Patterns: idempotency, retries, timeouts, circuit breakers, async workflows, queues, eventual consistency
- Data design: relational vs NoSQL, caching, indexing, migrations, multi-tenant considerations
Linux & Containerization
- Confident with Linux commands (ps, top, systemctl, netstat, etc.) and networking basics.
- Strong Docker competence: Dockerfiles, multi-stage builds, image security, and container debugging.
Observability & Diagnostics
- Strong in structured logging, correlation IDs, and trace context.
- Experience with Datadog, Prometheus/Grafana, OpenTelemetry, or ELK stacks.