[Remote] Senior Backend Engineer ((Python / Go)
Note: The job is a remote job and is open to candidates in USA. RAPIDFORT is seeking a skilled and passionate Senior Backend Engineer to join their team, focusing on the design, development, and maintenance of high-performance, scalable microservices. The ideal candidate will have strong expertise in Go and a deep understanding of distributed systems architecture.
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
Skills
- Python (Deep expertise with frameworks like FastAPI, Flask, or Django)
- Go (Golang) (Experience building robust, high-concurrency microservices)
- Designing, developing, and deploying RESTful APIs
- Keycloak, API authentication, JWT
- Realtime analytics (Clickhouse)
- Relational databases (MySQL) including complex query optimization
- NoSQL databases (Redis)
- Kubernetes for deployment and scaling
- Docker container build
- Writing comprehensive unit, integration, and end-to-end tests
- 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
- Production microservices ownership (not just “worked on”)
- 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
- 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 (if relevant)
- Can take an ambiguous production issue and drive it to resolution
- Uses a structured approach: reproduce → isolate → instrument → hypothesis → validate → fix → prevent
- Confident with commands/tools like: ps/top/htop, journalctl, systemctl, netstat/ss, lsof, curl, grep/sed/awk, strace (bonus), log parsing
- Understands networking basics (DNS, TLS, ports, timeouts)
- Can explain Dockerfiles, layers, multi-stage builds, image size/security
- Debug containers: env vars, volumes, entrypoints, networking, resource limits
- Strong in structured logging, correlation IDs, trace context
- Metrics + tracing + logs as a system
- Datadog experience is a must-have, or a very credible equivalent (Prometheus/Grafana + OpenTelemetry + ELK) with proof they can ramp fast
- CI/CD, release processes, rollback strategies
- Basic security and reliability hygiene (secrets mgmt, least privilege, rate limiting)
- 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
- 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
Benefits
- 401(k) retirement plan
- Health, dental, and vision insurance
- Paid time off (PTO) and company holidays
- Flexible work arrangements
- Professional development and training support
- Performance-based bonuses (if applicable)
Company Overview
Company H1B Sponsorship