AI Solutions Engineer, Office of the Group CEO

The Caravel Group, headquartered in Hong Kong, is a privately held and globally diversified group with operations across maritime services, dry bulk commodity trading, institutional investment management, and philanthropy.

Its maritime division includes Fleet Management Limited, the world’s second-largest ship management company with over 600 vessels under technical management and over 120 vessels under Newbuilding supervision. Caravel also owns the International Maritime Institute (IMI) in India, reinforcing its commitment to maritime talent development.

Through Caravel Asset Management, the Group invests globally across public markets and private equity, while its philanthropic arm, The Caravel Foundation, supports the education and well-being of underprivileged youth across Hong Kong, China, and India.

Job Position Summary

Caravel is scaling AI as a core capability across the group and treating it as mission‑critical software: secure, scalable and supportable. This is a highly autonomous, hands‑on role in the CEO’s office focused on practical AI tools that improve executive productivity and decision speed.

As an AI Solutions Engineer, Office of the Group CEO, you will turn ambiguous executive problems into dependable software, AI‑enabled workflows and decision‑support tools. This is not a research or prompt‑only role; it is about extracting data, building useful applications, applying sound analytics where helpful, and shipping production‑grade solutions.

You will work closely with Fleet Management Limited (FML) Technology to align with production standards, governance and support expectations while delivering tangible value to the Group CEO.

Key Role and Responsibilities

As the AI Solutions Engineer, Office of the Group CEO, you will be the primary technical partner responsible for building practical AI tools and workflows that reduce information latency and support faster strategic decisions.

This is a builder role focused on turning high‑level goals into working tools, prototypes and production‑ready services using LLMs, agentic AI, data engineering and strong software discipline. It is not an architecture‑only or research role; success is measured by reliable solutions that work day‑to‑day. Your day will typically include:

Agentic AI Development and Intelligent Data Extraction

• Design and build autonomous agents and data pipelines that pull, structure and synthesise information from internal systems, corporate data sources and relevant external platforms
• Build executive dashboards, reports and tools that combine data across functions and provide clear, low‑latency insight for decision‑making

Build production‑grade AI and data solutions

• Design, build and maintain backend services, data pipelines and platform components that support AI workloads at scale
• Apply practical analytics, forecasting and light machine learning where they materially improve decision quality
• Implement shared platform capabilities such as environment provisioning, configuration, secrets management and deployment pipelines
• Apply strong engineering practices including version control, testing, CI/CD and clear documentation
• Ensure solutions align with FML technology standards, security requirements and architectural guardrails

Navigate prototypes and AI systems into production

• Build and operate MLOps / LLMOps pipelines for packaging, versioning, deployment, monitoring and rollback
• Rapidly prototype bespoke tools for the CEO, then mature successful ones into production services with clear ownership
• For Fleet use cases involving PARIS (in‑house developed ERP), route changes through the right governance channels and transition productionised solutions into Fleet ownership; retain ownership of Caravel‑specific tools

Anchor reliability, scalability, and support

• Work with FML Technology teams, including Cybersecurity and Operations, to define runbooks, support models and incident response processes
• Apply security‑by‑design principles, including access control, data protection and environment segregation
• Continuously improve platform robustness, performance and cost efficiency

Relationship

INTERNAL:

• Office of the CEO (Caravel) strategic priorities, prototyping needs, and delivery outcomes
• Fleet Management Limited Technology teams – standards, architecture, security, production readiness, and transition of Fleet/PARIS solutions into managed ownership
• Business, finance, research, and operational stakeholders across Caravel and Fleet for problem definition, data validation, and tool adoption

EXTERNAL:

• Cloud and AI platform vendors (AWS, Microsoft, Google Cloud)
• External data and information providers such as Bloomberg, Clarksons, S&P Global, and other specialist sources as required

Job Experience, Functional Knowledge and Qualifications

ESSENTIAL:

• 6+ years of hands‑on experience as a software, platform, AI or data engineer, with evidence of delivering production‑grade tools
• Hands‑on experience with AI / LLM capabilities, including deploying and operating them in real systems, with familiarity in agent frameworks, RAG, vector stores and tool orchestration
• Strong experience building APIs, backend services and data pipelines across documents, analytics platforms, AI services and internal or external data sources
• Practical experience using analytics and light machine‑learning techniques where useful, with strong Python skills for backend services, automation and data handling
• Practical cloud engineering experience (AWS, Azure or Google Cloud), including deploying and operating services in production
• Strong grounding in modern engineering practices including CI/CD, testing, version control, infrastructure automation and core MLOps / LLMOps disciplines
• Ability to build clear C‑suite visualisations and interfaces that support real decision‑making
• Experience designing systems for reliability, scalability, security and operational support when handling sensitive commercial or operational data
• Degree in Computer Science, Engineering, Data, Mathematics or a similar technical discipline

DESIRABLE:

• Experience with MLOps / LLMOps tooling (e.g., MLflow, Kubeflow, model registries, evaluation pipelines)
• Familiarity with containerisation and orchestration (Docker, Kubernetes)
• Experience building tools for senior executives, trading, research, or other high‑consequence decision environments
• Experience working in regulated or operationally critical environments and with specialist market or maritime data sources

The Caravel Group is committed to diversity, equity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by local laws.