Software Engineer, Backend Developer, Cloud Engineer - Software

Lucidya is a leading AI-powered Customer Experience Management (CXM) platform in the MENA region, enabling enterprises to understand, engage, and serve customers across digital channels at scale.

As we move toward IPO-scale, we are rebuilding parts of our platform to achieve:

• Extreme reliability (SLO-driven engineering)
• High-scale distributed processing (billions of data points)
• AI-native architecture (LLM + real-time intelligence)

We don’t optimize for titles, we optimize for impact! Whether you are junior or senior doesn’t matter and what matters is your ability to move faster and think deeper than the average engineer. We operate with extreme ownership. Problems don’t belong to teams or tickets where they belong to whoever sees them. The right person for this role doesn’t walk past a broken system.

If something is failing, you fix it even if it’s not “your job.”

• Design and operate high-throughput, event-driven pipelines across a 100+ microservice ecosystem handling billions of data points
• Build and scale distributed messaging systems with Rabbit
  
  MQ, back pressure management, consumer scaling, and queue health
• Develop and maintain API gateway layers with advanced routing (multi-upstream, traffic splitting, environment isolation)
• Architect SSO and identity federation for enterprise clients, supporting multi-IdP routing with zero coupling to core services
• Define clean service boundaries across ingestion, processing, and delivery pipelines spanning Ruby and Python

• Diagnose and resolve complex production issues (e.g., deadlocks, queue exhaustion, connection pool saturation) — and eliminate root causes
• Optimize Postgre
  
  SQL for heavy write workloads, contention management, schema design, triggers, and connection scaling
• Design and tune Elasticsearch for search, indexing, and real-time Arabic relevance at scale
• Make informed trade-offs between multi-process and async architectures based on workload characteristics

• Build and maintain observability across a large-scale system using Grafana, Loki, distributed tracing, and SLOs
• Own production incidents end-to-end, tracing failures across queues, search systems, and external integrations
• Lead root cause analysis and implement preventative measures across multi-service pipelines
• Build internal tooling that improves engineering velocity, automation, deployment gating, and review enforcement
• Turn architectural principles into enforceable standards and guardrails, not just documentation

• Drive platform decoupling and service isolation across the system
• Contribute to Kubernetes migration and infrastructure modernization
• Standardize and improve CI/CD pipelines across services

Ruby on Rails
· Python
· PostgreSQL
· Elasticsearch
· Redis
· RabbitMQ
· Kubernetes
· AWS / GCP
· APISIX
· Grafana + Loki

• Strong foundation in distributed systems. You understand failure modes before you write the first line
• Hands‑on experience with event‑driven architecture and message queues in production
• Deep comfort with concurrency, back pressure, and fault tolerance
• Track record debugging complex production issues — not just fixing them, preventing them
• Experience with Rails or Python backends at meaningful scale
• You improve systems you weren’t asked to touch

• Read and understand an existing codebase by week one
• See a broken system and fix it before anyone asks you to
• Have strong opinions about architecture and can back them up with data
• Think in systems: latency, throughput, failure modes, and cost at scale
• Treat documentation, tests, and observability as non‑negotiable defaults and not afterthoughts
• Ship fast and without breaking things. Speed and quality are not a trade‑off for you
• Consistently exceed expectations where meeting the bar is a floor, not a target
• Are hungry for hard challenges and actively seek problems at the edge of your limits
• Feel a sense of urgency that doesn’t require external pressure
• Have rebuilt or stabilised something significant and can talk about it concretely

• Real scale with billions of events and not just toy systems
• Direct impact at CTO and executive level
• Pre‑IPO with clear trajectory and your work has real impact on clients