Location:
Singapore (hybrid) •
Reports to:
CTO
About Rida
Join us in shaping the future of logistics by building the backend systems and cloud infrastructure that power real-time, AI‐driven delivery optimisation.
The Role
You’ll design and scale core services, production‐grade deployment pipelines, and model‐serving infrastructure that stay reliable under dynamic, high‐throughput workloads.
You’ll bridge software engineering and platform operations so our AI and ops products thrive in production.
Key Responsibilities
Backend services
Design, build, and maintain modular services in
Node.js and/or Python .
Ship secure, high‐performance
REST/GraphQL
APIs with auth ( OAuth2/JWT ), rate limiting, and caching.
Architect cloud‐native infrastructure to support AI model training, deployment, and continuous delivery.
Use Docker, Kubernetes, and infrastructure‐as‐code tools to build robust, modular environments.
Develop scalable endpoints and backend systems for real‐time and batch AI model inference, including model versioning, A/B testing, and rollback mechanisms.
Manage cloud compute and GPU with autoscaling and cost optimization on AWS/GCP/Azure.
Reliability & observability
Implement monitoring and alerting systems (Prometheus, Grafana, ELK, OpenTelemetry) to ensure high availability and rapid diagnostics across models and APIs.
Design health checks, logging pipelines, and automated incident diagnostics.
Quality & delivery
Write and maintain unit, integration, and end‐to‐end tests using Jest, PyTest, Postman, or similar frameworks to guarantee code quality and system stability.
Qualifications
5+ years
in backend or platform engineering (startup/SaaS/AI environments ideal).
Technical Mastery:
Strong knowledge of Node.js, Python, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
Familiarity with GPU workloads and ML deployment a plus.
Quality‐Focused:
Solid experience writing robust test suites and designing systems for observability and fault tolerance.
Analytical & Systems Thinker:
Ability to design solutions that are scalable, maintainable, and cost‐efficient.
Collaborative:
Eager to work cross‐functionally with AI engineers, data scientists, and operations teams in a fast‐paced environment.
What We Offer
Impact:
Your systems directly power our AI scheduling and delivery optimisation at scale.
Growth:
Deep exposure across backend, DevOps, and MLOps; high‐ownership projects.
Compensation:
Market‐aligned salary, benefits, performance bonus; ESOP optional.
Environment:
Work with a small, ambitious team at the intersection of AI, operations, and engineering.
How to apply
Email
and
with your CV and a short note about a reliability or scalability win you’re proud of (problem → approach → impact).
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