Senior Backend Engineer

RapidFort

Location: Location not stated
Workplace: Remote
Employment: Full Time
Salary: USD 140,000–200,000/yr

Posted 3mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

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

Requirements

Deep expertise with Python frameworks like FastAPI, Flask, or Django
Expertise in Go (Golang) for building robust, high-concurrency microservices
Designing, developing, and deploying RESTful APIs
Proficiency with Keycloak, API authentication, JWT
Expertise in Realtime analytics (Clickhouse)
Expertise in Relational databases (MySQL) including complex query optimization
Expertise in NoSQL databases (Redis)
Expertise in Kubernetes for deployment and scaling
Expertise in Docker container build
Writing comprehensive unit, integration, and end-to-end tests
7+ years of professional experience in backend software development
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”)
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 (senior bar)
Can design systems with tradeoffs: latency, throughput, cost, reliability
Familiarity with patterns: idempotency, retries, timeouts, circuit breakers, async workflows, queues, eventual consistency
Data design: relational vs NoSQL, caching, indexing, migrations, multi-tenant considerations
Strong debugging & problem-solving in real-world scenarios
Can take an ambiguous production issue and drive it to resolution
Uses a structured approach: reproduce → isolate → instrument → hypothesis → validate → fix → prevent
Confident with Linux 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
Experience with CI/CD, release processes, rollback strategies
Basic security and reliability hygiene (secrets mgmt, least privilege, rate limiting)

Preferred

Experience setting up and maintaining automated deployment pipelines
Proficiency with monitoring and logging tools
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

Skills

Python
FastAPI
Flask
Django
Go
Golang
RESTful APIs
Keycloak
API authentication
JWT
Clickhouse
MySQL
Redis
Kubernetes
Docker
Git
AWS
Azure
GCP
Datadog
Prometheus
Grafana
OpenTelemetry
ELK

Responsibilities

Requirements

Preferred

Skills

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