About the job
We are seeking a highly skilled DevOps Specialist to architect, implement, and maintain end-to-end CI/CD pipelines using GitHub, with a strong focus on test-driven deployment, automated release management, and Infrastructure as Code (IaC) practices.
The ideal candidate will containerize services using Docker, manage build, compilation, and publishing workflows for JavaScript, TypeScript, and C++ packages, and design robust multi-language build pipelines leveraging CMake or similar build tools.
The role also includes automating build, tagging, and publication processes across web, desktop, and mobile platforms to ensure consistent and traceable releases. Deep expertise in Linux system administration, networking, and IaC tools is essential to deliver scalable, secure, and highly available deployments.
Responsibilities
•Lead the design, architecture, and management of CI/CD pipelines using GitHub Actions (and similar tools), ensuring fast, reliable, and reproducible software delivery.
•Implement and enforce test-driven deployment systems, integrating automated testing, validation, and monitoring to maintain code quality and accelerate feedback cycles.
•Containerize applications and microservices with Docker, optimize image builds, and manage deployment pipelines for distributed environments.
•Oversee the build, packaging, and publishing lifecycle for JavaScript, TypeScript, and C++ packages, including versioning, semantic tagging, and NPM or internal registry publication.
•Develop and maintain cross-platform build pipelines using CMake or equivalent tools, ensuring consistent compilation and release workflows across web, desktop, and mobile.
•Automate end-to-end release processes, including tagging, building, signing, and distributing mobile, web, and desktop applications.
•Define and manage Infrastructure as Code (IaC) to provision and maintain reliable, scalable, and secure infrastructure environments.
•Collaborate closely with development, QA, and operations teams to troubleshoot deployment issues, optimize performance, and improve release reliability.
•Continuously improve observability and feedback loops, leveraging monitoring and alerting systems to maintain operational excellence.
Mandatory
•Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
•3+ years of hands-on experience architecting and maintaining CI/CD pipelines using GitHub Actions or equivalent tools at scale in a production environment.
•Strong proficiency in test-driven deployment methodologies, including writing and maintaining automated test suites for integration and end-to-end validation.
•Expertise in containerization technologies such as Docker, including image creation, registry management, and basic orchestration patterns.
•Experience managing package lifecycles for JavaScript and TypeScript, including versioning, compilation, semantic tagging, and publishing workflows to NPM.
•In-depth knowledge of C++ build systems, specifically CMake, with proven experience optimizing native build and deployment pipelines.
•Advanced Linux system administration and networking skills, including shell scripting, package management, performance troubleshooting, firewalls, and VPN configuration.
•Excellent communication, problem-solving, and collaboration skills, with the ability to work effectively in globally distributed teams.
•Experience with Infrastructure as Code (IaC) tools such as Terraform, Ansible, AWS CDK or AWS CloudFormation.
•Experience with mobile CI/CD automation, including build, tagging, and publication for iOS and Android applications.
•Advanced knowledge of release management practices, including automated versioning, signing, and artifact distribution.
Preferred
•Exposure to observability and monitoring systems, leveraging tools like Prometheus, Grafana, or ELK for deployment health tracking.
•Experience working in high-availability, security-sensitive environments, especially in fintech, blockchain, or distributed systems contexts.
•Experience deploying and managing blockchain-based applications.
•Exposure to AI/ML pipelines, including automated model training, evaluation, and deployment using frameworks like PyTorch or TensorFlow.
