About the role
The candidate will have responsibilities across the following functions:
Engineering Leadership and Architecture:
- Lead Engineering, ML/Data Science, and Analytics teams.
- Define technical vision, architecture, and engineering standards.
AI, ML and Data Strategy:
- Build and scale production-grade AI/ML systems.
- Drive MLOps, model lifecycle management, data pipelines, and real-time data platforms.
- Deploy AI capabilities that create measurable customer and business impact.
Team Building and Organisational Leadership:
- Hire, mentor, and grow senior engineering leaders.
- Build a high-performing engineering culture.
- Define ownership, accountability, and clear team structures.
Product and Business Partnership:
- Partner closely with CEO, Product, Sales, and Customer Success teams.
- Convert customer problems into scalable technical solutions.
- Align engineering roadmap with business priorities and revenue goals.
Requirements:
- 10+ years of experience in Software Engineering, Data Engineering, or Machine Learning.
- Experience leading Engineering, ML/Data Science, and Analytics organisations.
- Leadership experience in high-growth B2B SaaS or startup environments.
- Experience working directly with Product and Business leadership.
Technical Expertise:
- Strong backend engineering and distributed systems expertise.
- Experience designing scalable cloud-native architectures.
- Production experience with AI/ML systems (not just research).
AI and Data:
- Experience deploying LLM/GenAI/ML solutions into production.
- Experience building AI-powered products with measurable business outcomes.
- Strong understanding of AI platform architecture and data pipelines.
Preferred Domain Experience:
- Logistics / Supply Chain Technology (strongly preferred).
- Transportation Visibility Platforms.
- Fleet Management.
- Supply Chain SaaS.
- Data-heavy B2B SaaS platforms.
- Enterprise / Fortune 500 customer-facing products. =