Company Overview:

Our client is a technology company building a next-generation, AI-native enterprise platform for the global maritime and shipping industry. Its first product is being developed for a leading Singapore-based shipping company, with stakeholders across Singapore, India, Europe, and the United States. The platform will combine artificial intelligence, cloud computing, mobile and offline capabilities, automation, analytics, IoT, and up-to-date enterprise architecture.

Our vision is to build a globally scalable technology platform that transforms maritime operations and can support future enterprise products.

Position Summary:

The Founding CTO will be a key member of the leadership team and will define and execute the company's technology strategy. The CTO will be responsible for designing the AI-native platform architecture, selecting the technology stack, establishing engineering and cybersecurity standards, planning phased product delivery, and building a high-performing engineering organization. This role requires a hands-on strategic leader who can balance innovation, delivery speed, scalability, security, and cost.

Key Responsibilities:

Technology Strategy and Architecture:

- Define the company's technology vision, architecture principles, and long-term roadmap.
- Design a secure, scalable, cloud-native and AI-first enterprise platform.
- Select the appropriate technology stack, cloud platform, databases, development frameworks, and AI technologies.
- Establish a platform-first architecture that supports phased delivery of individual ERP modules.
- Define mobile-first, web-based, API-first, event-driven, and offline-capable architecture.
- Ensure the platform supports scalability, high availability, low latency, disaster recovery, and global operations.

AI, Data and Innovation:

- Define the AI strategy and ensure AI is built into the platform from the beginning rather than added later.
- Plan capabilities such as enterprise AI assistants, intelligent workflows, predictive analytics, document intelligence, anomaly detection, and decision support.
- Define the architecture for LLMs, AI agents, enterprise knowledge, vector search, and secure data access.
- Establish AI governance covering accuracy, security, human approval, monitoring, compliance, and responsible use.




- Optimize AI performance and costs through appropriate model selection, model routing, caching, token controls, and usage monitoring.
- Evaluate emerging technologies and recommend build-versus-buy decisions.

Cloud, Integration and Cybersecurity:

- Define the cloud and infrastructure strategy across AWS, Azure, or GCP.
- Use serverless, containerized, and edge infrastructure appropriately based on workload requirements.
- Establish integration standards for legacy ERP systems, AIS, IoT sensors, finance platforms, document systems, and external services.
- Define API, data synchronization, and onboard-to-cloud connectivity standards.
- Establish cybersecurity policies covering identity, access control, encryption, audit trails, monitoring, threat detection, and disaster recovery.
- Ensure enterprise-grade security and compliance are incorporated throughout the development lifecycle.

Engineering Leadership and Delivery:

- Build and lead a multidisciplinary engineering organization across platform, backend, web, mobile, AI, data, integration, DevOps, security, and quality assurance.
- Establish engineering standards, development processes, architecture governance, testing, CI/CD, documentation, and release practices.
- Translate business requirements into practical, scalable technology solutions.
- Work closely with product, business, UX, maritime domain experts, and client stakeholders.
- Lead technical discussions during discovery, implementation planning, and executive reviews.
- Ensure measurable, usable capabilities are delivered through a phased implementation approach.

Team Planning and Cost Optimization:

- Develop a phased organization and hiring roadmap aligned with platform and module delivery.
- Identify which skills are required internally and which can be supported through specialist partners or contractors.
- Avoid premature hiring by expanding the team based on delivery priorities and business needs.
- Prepare technology budgets and monitor infrastructure, engineering, licensing,



and AI operating costs.
- Optimize costs without compromising security, quality, scalability, or long-term maintainability.
- Establish transparent metrics for engineering productivity, cloud consumption, AI usage, and total cost of ownership.

Key Deliverables During the First Six Months:

- Technology vision and product roadmap.
- AI-native platform and reference architecture.
- Platform-first, phased implementation plan.
- Cloud, infrastructure, and disaster recovery strategy.
- Enterprise data, API, integration, and offline-sync architecture.
- AI strategy, model approach, governance, and cost-control framework.
- Cybersecurity and access-control framework.
- Engineering standards, DevOps model, and CI/CD pipeline.
- Phased team structure, hiring plan, and partner strategy.
- Initial technology budget and total cost-of-ownership framework.
- Architecture and delivery plan for the first usable business module.

Qualifications:

- Bachelor's or Masters degree in Computer Science, Software Engineering, or a related field.
- 15+ years of software engineering experience, including senior technology leadership.
- Proven experience designing and delivering large-scale SaaS, ERP, or enterprise platforms.
- Strong expertise in cloud-native architecture, APIs, distributed systems, databases, DevOps, cybersecurity, and enterprise integration.
- Practical understanding of modern AI platforms, LLMs, RAG, AI agents, vector databases, analytics, and AI governance.
- Experience building mobile-first, offline-capable, or globally distributed applications.
- Experience planning and scaling multidisciplinary engineering teams in phases.
- Strong commercial understanding of technology investment, infrastructure costs, vendor selection, and build-versus-buy decisions.
- Maritime, shipping, logistics, transportation, manufacturing, or asset-intensive industry experience would be advantageous.

Key Competencies:

- Strategic technology leadership.
- AI-native product and platform thinking.
- Enterprise and solution architecture.
- Cloud, data, integration, and cybersecurity.
- Engineering team building and mentoring.
- Phased delivery and cost management.
- Product and stakeholder collaboration.
- Clear executive communication.
- Innovation with practical business judgment.

📌 Founding Chief Technology Officer (India)
🏢 MAXIC ARROW
📍 India