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In this role, you will design, build, and maintain high performance web applications and cloud software tailored for maritime automation and telemetry. You will work on full lifecycle software development, from architecting secure backend APIs on Linux servers to creating rich, responsive frontend user interfaces. You will also lead the integration of AI into our ship automation configurator software, so that engineers can work with it through natural language and AI agents, and so that customer requirements can be turned into configurations automatically. You will be the company's first
AI engineer: you will not inherit an existing AI architecture, but will evaluate the options, choose the approach, and own the result.
Your Responsibilities:
- Web & Cloud Development: Design, build, and deploy robust, high-performance web applications using .NET (ASP.NET Core) on the backend and React on the frontend.
- Database & Infrastructure: Design, optimize, and manage PostgreSQL relational databases hosted on Linux server environments.
- System Architecture & UI/UX: Create modern graphic screen layouts and intuitive user interfaces for real-time vessel monitoring and control systems.
- Network & Protocols: Research, design, and integrate communication protocols between web software and marine hardware devices.
- AI Technical Ownership: As the company's first AI engineer, survey the available approaches (e.g. prompting vs. RAG vs. fine-tuning, single agent vs. fixed workflow, hosted vs. self-hosted models, build vs. buy), choose the right one for each problem, and document the trade-offs behind each decision.
- AI Assistant Integration: Design and build an AI assistant inside our existing ship automation configurator, allowing engineers to describe tasks in natural language and have the AI carry them out.
- Agentic Workflows: Build AI agents that use tool calling to read and change configurations through the configurator's APIs, working in a plan, act, and verify loop similar to an AI coding harness, with human review and approval of changes.[GU1.1]
- Internal Enablement: Advise management on what AI can and cannot do, set realistic expectations and priorities, and share knowledge so that colleagues can use and maintain AI features safely.
- End-to-End Delivery: Collaborate directly with Project Engineering teams to define requirements, build custom features, and deliver software modules on schedule.
- Quality & Reliability: Independently write, unit test, and document modular, scalable, and maintainable code for safety-critical applications.
- Domain Leadership: Act as a subject matter expert for assigned software modules and stay ahead of industry trends in web technologies and maritime automation.