• Develop and maintain backend services using Go • Contribute to integration of services across the platform • Support the design and implementation of data transformation processes • Help optimize systems for performance, reliability, and scalability • Work with containerized environments using Kubernetes and Terraform • Follow best practices for code quality, security, and observability • Assist in building and maintaining monitoring solutions • Troubleshoot and resolve issues related to integration, data processing, and deployments • Collaborate with engineering and architecture teams on technical solutions

• Design and implement backend-heavy features using TypeScript and Node.js • Build and evolve REST APIs, focusing on correctness, consistency and clear boundaries between services • Work with SQL (PostgreSQL): data modeling, migrations, and consistency guarantees • Participate in tech spikes: explore unclear problems and turn them into concrete technical plans • Take full ownership of one or more services - from requirements and implementation to production support • Help drive integration work with external partners (vendors, clients) when needed • Work with production systems: investigate incidents, debug API failures, analyze data issues • Improve observability: logs, metrics, visibility into system behavior • Identify weak spots in reliability, performance or monitoring and propose improvements • Apply reliability patterns: timeouts, retries, idempotency, graceful degradation • Handle incidents responsibly and help improve processes to prevent problems to occur again • Collaborate with Product and EM to clarify requirements and reduce ambiguity early • Contribute to technical discussions, raise risks, explain trade-offs and propose balanced solutions • Review code and mentor mid-level engineers • Share knowledge via pairing, documentation and internal discussions • Help improve engineering practices: testing, code quality, reliability patterns • Contribute to React code when features require UI updates or customer-facing flows

• Design, develop, and maintain enterprise-grade backend services using Node.js, TypeScript, and NestJS. • Architect and implement high-performance REST and SOAP APIs for complex enterprise integrations. • Optimize PostgreSQL databases for high availability, partitioning, replication, and performance tuning. • Define and enforce secure coding practices, design patterns, and architectural principles. • Collaborate with DevOps, frontend, QA, and product stakeholders to ensure seamless integration and delivery. • Troubleshoot production issues, enhance reliability, and implement performance tuning at scale. • Lead code reviews, enforce coding standards, and integrate quality gates in CI/CD pipelines. • Mentor client engineering teams, contribute to technical strategy and architecture decisions. • Integrate external systems, tools, and services to extend backend capabilities. • Provide continuous innovation by adopting cloud-native, serverless, and emerging backend technologies.

About us: Soar is a global fintech startup that specializes in financing and investment. Currently headquartered in Saudi Arabia, Soar is growing throughout the region with a mission to help people achieve their financial goals with innovative financial and property investment solutions and tools through its multi-purpose platform, designed to offer a simple and seamless user experience. Role Summary: This role is for engineers who operate at a higher abstraction level. You will design, manage, and optimize AI agents that generate code, workflows, and business logic. Your responsibility is to ensure outputs are correct, scalable, and aligned with business goals. You are expected to: - Reduce development time through AI - Improve output quality through validation and iteration - Continuously refine agent performance Key Responsibilities: - Design and manage agent-based development workflows - Oversee AI-generated code: validate, test, refactor, and productionize - Build systems to evaluate agent output quality and reliability - Fine-tune prompts, tools, and pipelines to improve outcomes - Integrate AI agents into the software development lifecycle (SDLC) - Translate business problems (mortgage, real estate workflows) into AI-driven solutions - Establish best practices for multi-agent collaboration and orchestration - Monitor performance, cost, and accuracy of AI systems - Work across product and business teams to identify automation opportunities