Role Description As a Backend Staff Engineer, you will be responsible for driving the technical standards for the Backend in our Last Mile Delivery domain. You will work closely with multiple squads within the domain to provide technical leadership in areas such as: - Tech roadmaps - Architecture decisions - Feature development and release cycles Your role will also involve mentoring junior developers and contributing to the scaling up of Backend engineers in multiple squads, which includes: - Conducting technical interviews to identify and onboard talented engineers - Designing, building, and maintaining features for domain applications - Providing technical leadership and managing dependencies - Conducting design and code reviews - Supporting and helping grow domain team members by assisting with technical blockers - Continuously discovering, evaluating, and implementing new technologies to improve efficiency - Participating in architecture and design discussions - Contributing to building the technical roadmap - Improving engineering standards, tooling, and processes - Conducting feasibility studies to validate capability and functionality - Drafting and submitting intellectual property - Conducting research and assessing current technologies - Developing and executing complex, multi-tier distributed software search applications - Applying technical and domain expertise to products and problems - Assessing and writing code to improve or extend applications - Managing and providing assistance for current software applications - Providing technical leadership and mentorship to others Qualifications - 8+ years of experience - Solid backend engineering experience with Node.js and Go - Strong foundation in programming fundamentals - Excellent communication skills - Proven problem-solving abilities and a willingness to help others achieve their goals - Extensive experience with Git in a team environment - Proficiency in writing testable code and unit tests - Bonus: Experience in a fast-growing startup in the on-demand services industry - Extensive experience with A/B experiments and a data-driven approach to product development Company Description Yassir is the leading super App in the Maghreb region set to change the way daily services are provided. It currently operates in 45 cities across Algeria, Morocco, and Tunisia with recent expansions into France, Canada, and Sub-Saharan Africa. It is backed by approximately $200M in funding from VCs from Silicon Valley, Europe, and other parts of the world. We offer on-demand services such as ride-hailing and last-mile delivery. Building on this infrastructure, we are now introducing financial services to help our users pay, save, and borrow digitally, helping usher the continent into a digital economy era. We’re not just about serving people - we’re about creating a marketplace to bring people what they need while infusing social values.

• Collaborate with stakeholders throughout the SDLC to translate requirements into high-quality, reliable, cost-effective, and maintainable solutions that solve customer problems and generate business outcomes. • Design, develop, and implement high quality software components with a focus on Continuous Delivery principles and practices. • Champion integrated engineering practices within the organization, fostering collaboration and shared ownership between development, operations, and security teams. • Deliver technical and administrative support for live applications, promoting automation and proactive monitoring and self-recoverability, rapid incident response, and continuous improvement. • Analyze existing systems and processes to identify bottlenecks and opportunities for improvements to flow. • Own the configuration management of software items and their dependencies, utilizing Infrastructure as Code (IaC) tools. • Collaborate on developing and implementing a measurement strategy for tracking key performance indicators (KPIs) related to software delivery and performance.

• Develop and maintain backend functionality in a PHP-based payment processing platform. • Contribute to the gradual migration of selected systems from PHP to Rust. • Troubleshoot production issues and perform data investigations when needed. • Participate in weekly production releases and help maintain stable deployment cycles. • Review code and collaborate with engineers to maintain code quality. • Support and evolve system observability through logging, monitoring, and debugging tools. • Work closely with the team to understand and maintain complex payment workflows tied to government systems.

Senior Distributed Systems Engineer / Architect Series A Cybersecurity Company — RapidFort Location: Remote / Hybrid Type: Full-time About RapidFort RapidFort is a Series A cybersecurity company backed by $42M from leading investors, building the next generation of container and software supply-chain security. Our platform helps enterprises and U.S. government agencies eliminate vulnerabilities in container images, secure Kubernetes environments, and protect cloud-native infrastructure at runtime. Due to our work with DoD and U.S. federal customers, U.S. citizenship is required for this role. Overview We are looking for a Distributed Systems Engineer / Architect to design and build highly scalable custom systems that process large volumes of data across CPU, disk, and network intensive workloads. This role is deeply hands-on and requires strong systems thinking, algorithm design, and performance optimization skills. You will work on core infrastructure and algorithms, building systems that maximize resource utilization across distributed environments. The ideal candidate enjoys working close to the metal, writing efficient code and tooling (primarily in Python and Bash) while building the instrumentation needed to continuously measure, analyze, and improve system performance. This role requires a data-driven mindset and a passion for building reliable, scalable systems from first principles. Responsibilities System Architecture Design and implement scalable distributed systems that handle heavy CPU, disk, and network workloads. Architect systems for high throughput, reliability, and efficient resource utilization. Develop distributed algorithms and data processing pipelines. Performance & Optimization Analyze system behavior to identify bottlenecks across compute, storage, and network layers. Optimize workloads for maximum efficiency and minimal resource waste. Develop strategies for parallelization, batching, and workload scheduling. Engineering & Implementation Implement system components and tooling primarily in Python and Bash. Build custom orchestration, automation, and distributed job execution mechanisms. Write efficient algorithms and low-level logic to manage large-scale workloads. Observability & Data-Driven Engineering Build instrumentation, metrics, and telemetry to measure system performance. Develop dashboards and analysis workflows to guide optimization decisions. Use empirical data and experimentation to improve system behavior. Infrastructure & Reliability Design systems that operate reliably across distributed environments. Implement monitoring, debugging, and recovery mechanisms for large-scale systems. Collaborate with infrastructure and platform teams to ensure smooth deployment and operation. Requirements Core Experience Strong experience building distributed systems or large-scale backend infrastructure Deep understanding of systems performance (CPU, memory, disk I/O, networking) Experience optimizing workloads for throughput and efficiency Programming Strong Python development skills Strong Bash / shell scripting Ability to implement and reason about algorithms and system-level logic Systems Knowledge Experience with parallel processing, distributed job execution, or large data pipelines Familiarity with Linux systems, resource scheduling, and performance tuning Understanding of networked systems and distributed coordination Engineering Approach Strong data-driven mindset with focus on measurement and experimentation Experience building observability, metrics, and instrumentation Ability to debug complex systems in production environments Nice to Have Experience with high-performance computing (HPC) workloads Experience with containerized environments (Docker/Kubernetes) Background in large-scale data processing or distributed compute frameworks Familiarity with performance profiling tools and system tracing What You’ll Work On Designing custom distributed compute frameworks Building efficient algorithms to process large-scale data workloads Optimizing compute pipelines across CPU, disk, and network resources Developing instrumentation and performance analytics Improving system efficiency through continuous measurement and experimentation Base Salary: $170,000 to $200,000