Microservice Backend Engineer (Python/Go)

RapidFort, Inc.
5h$120,000 - $200,000

About The Position

We are seeking a skilled and passionate 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 both Python and Go (Golang), and a deep understanding of distributed systems architecture.

Requirements

  • U.S. citizenship required due to federal contract requirements (No active security clearance needed at time of hire)
  • 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.
  • 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.
  • Writing comprehensive unit, integration, and end-to-end tests.
  • 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
  • System design & architecture (senior bar)
  • 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)
  • 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
  • Linux fundamentals (practical, daily-use)
  • 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)
  • Docker + container runtime competence
  • Can explain Dockerfiles, layers, multi-stage builds, image size/security
  • Debug containers: env vars, volumes, entrypoints, networking, resource limits
  • Observability / logging / diagnostics
  • 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
  • Platform maturity
  • CI/CD, release processes, rollback strategies
  • Basic security and reliability hygiene (secrets mgmt, least privilege, rate limiting)
  • Coding in Python - senior architecture + prod ops + observability.

Nice To Haves

  • 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.

Responsibilities

  • Design, implement, and maintain scalable and reliable backend microservices using Python and 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.
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