About ShipIn
ShipIn Systems is the world's first FleetVision Platform, unlocking ship-to-shore collaboration for global maritime fleets with AI-powered maritime CCTV and visual analytics. Our platform proactively alerts shipowners, managers, and seafarers to onboard events in real time, enhancing safety, security, and operational efficiency across fleets worldwide.
About the role
We are seeking an experienced Senior Platform Engineer, Deployment Automation to join our R&D Systems Engineering team, reporting to the Director of Systems Engineering. This role is instrumental in leading the transformation of our deployment infrastructure by adopting modern automation and continuous delivery practices.
This role will be instrumental in leading deployment activities, improving automation processes, and enhancing our customer onboarding experience. Initially, you will spearhead the selection and deployment of a central system to support our deployment infrastructure.
Key Responsibilities
- Automation Development & Tooling: Develop, maintain, and own the suite of Python-based orchestration tools and APIs to streamline the end-to-end product delivery process.
- Deployment Architecture (CI/CD/GitOps): Design, implement, and maintain scalable deployment architectures to enable robust one-touch deployment across on-premise solution, and edge systems.
- Kubernetes & Containerization: Manage and optimize application deployment within Kubernetes (K8s) clusters to guarantee high availability and resource efficiency.
- Cost & Efficiency: Lead technical activities to identify and implement resource efficiency improvements, including hardware validation and benchmarking (GPU/CPU), and optimizing container resource limits to meet cost reduction targets.
- Central System Leadership: Lead the evaluation, selection, and deployment of a new central information management system, ensuring robust integration with our automated deployment systems.
- System Lifecycle Management: Define and execute product lifecycle management processes (EoS, EoL, asset retirement, and replacement strategies) for customer assets and hardware.
Qualifications
- Minimum 5+ years of relevant experience in Platform Engineering, Deployment Automation, or Site Reliability Engineering (SRE) roles.
- Strong, verifiable proficiency and experience developing custom tooling and orchestration scripts using Python. Knowledge of Bash/Shell scripting is a strong asset.
- Mandatory hands-on experience deploying and managing applications within Kubernetes (K8s) and Docker.
- Proven ability to design and implement CI/CD pipelines (e.g., GitLab CI, GitHub Actions, Jenkins) and implement GitOps best practices.
- Specific experience automating deployment to hybrid SaaS and on-prem computer vision systems or physical edge devices.
- Experience conducting performance benchmarking and complex cost/performance analysis to inform strategic hardware selection decisions (GPU/CPU efficiency).
- Solid understanding of advanced networking concepts for deployment architecture (VLANs, DNS, routing, firewall rules) and familiarity with virtualization/Linux administration.
- Advantage: Familiarity with video streaming protocols (RTSP, ONVIF) and NVR system optimization is highly valuable.
- Demonstrated ability to understand and design solutions spanning the entire system lifecycle, including hardware, edge devices, NVRs, network components, and cloud services
