Backend Engineer 4 views

The role develops and maintains bus scheduling guidelines, ensures compliance with government transport regulations, and manages the operational data required for accurate scheduling and ticketing across the mobility platform.

Working closely with government transport authorities, bus operators, and the technology team, the role ensures that scheduling rules, route data, and fare structures are accurately implemented within the digital platform.

Through disciplined data governance and regulatory coordination, the role supports the reliable operation of the Smart Mobility e-ticketing and scheduling systems.

This role requires strong distributed systems capability, data modeling expertise, infrastructure awareness, and security-by-design discipline. The Backend Engineer owns service reliability, scalability, and maintainability across the full software lifecycle, from architecture through production operations.

The role operates within regulated financial environments and requires engineering rigor aligned with global best practices in fintech and high-availability systems.

• Design distributed, API-first backend services using modular and maintainable architectural patterns.
• Build horizontally scalable systems with fault tolerance and resilience built into service boundaries.
• Define clear service ownership, dependency management, and integration contracts.
• Apply structured architectural approaches to ensure testability, separation of concerns, and long-term maintainability.
• Document architectural decisions, trade-offs, and system constraints.

API Engineering and Service Lifecycle Ownership

• Design, implement, version, and maintain RESTful and event-driven APIs.
• Ensure backward compatibility and structured deprecation practices.
• Implement secure authentication and authorization mechanisms.
• Define service-level objectives including availability, latency, and error budgets.
• Own services from development through production monitoring and iterative improvement.

Data Architecture and Persistence

• Design relational and non-relational data models aligned with access patterns and scalability needs.
• Optimize query performance, indexing strategies, and transaction boundaries.
• Manage schema evolution and safe database migrations in live production environments.
• Ensure data integrity, consistency models, and durability guarantees are clearly defined.

Event-Driven and Streaming Systems

• Build asynchronous, event-driven services for loosely coupled system communication.
• Define and manage event schemas and lifecycle governance.
• Implement reliable message processing with retry strategies and failure handling.
• Design systems that balance consistency, throughput, and latency in distributed environments.

Performance, Scalability and Reliability Engineering

• Engineer systems for high throughput and low latency under real production load.
• Implement caching, rate limiting, and traffic management strategies.
• Apply resilience patterns including timeouts, retries, circuit breakers, and graceful degradation.
• Participate in load testing, stress testing, and performance profiling exercises.
• Contribute to service reliability metrics including uptime, mean time to recovery, and error rate reduction.

Security and Compliance by Design

• Implement secure coding standards and peer review practices.
• Enforce encryption in transit and at rest for sensitive data.
• Apply role-based access control and secure service-to-service communication.
• Ensure backend systems support auditability, logging, and traceability requirements.
• Collaborate with security teams to address vulnerabilities and compliance controls.

Artificial Intelligence Integration Support

• Design backend services that support model inference, scoring, and AI-enabled workflows.
• Ensure model outputs are auditable and traceable within transaction systems.
• Integrate streaming and batch pipelines that support AI-driven decision systems.
• Support monitoring of AI-related performance metrics where applicable.

Infrastructure-Aware Development and Cloud Operations

• Build containerized services and support orchestration in cloud-native environments.
• Design for deployment automation, configuration management, and rollback strategies.
• Ensure observability through structured logging, metrics instrumentation, and distributed tracing.
• Participate in production incident response and root cause analysis.
• Collaborate with DevSecOps and Site Reliability Engineering teams to improve operational maturity.

Engineering Excellence and Collaboration

• Participate in peer code reviews to maintain quality and consistency.
• Contribute to engineering standards, documentation, and reusable components.
• Actively manage technical debt and refactoring priorities.
• Work closely with Product Managers, Frontend Engineers, Data teams, and SRE to deliver end-to-end features.
• Engage in structured Agile ceremonies and delivery governance processes.

• Service availability and uptime against defined service-level objectives
• Reduction in production incidents and system failures
• Latency and throughput performance benchmarks
• Code quality and test coverage standards
• Security compliance and vulnerability resolution timelines
• Successful deployment frequency and rollback stability
• Documentation completeness and architectural clarity
• Contribution to reduced technical debt over time

• Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.
• Advanced certifications in cloud computing, distributed systems, or security are advantageous.

• Three to seven years of experience building and operating production backend systems
• Demonstrated experience with distributed systems and API development
• Experience working within Agile delivery environments
• Exposure to financial systems, regulated environments, or high-availability systems preferred
• Experience operating cloud-native infrastructure environments

• Distributed Systems Engineering
• Secure Engineering Discipline
• Data Architecture Expertise
• Cloud and Infrastructure Fluency
• Performance and Reliability Focus
• AI Integration Awareness
• Engineering Ownership and Accountability
• Collaborative Execution
• Continuous Improvement Mindset