Lead and scale distributed engineering teams (50+), owning backend, mobile (iOS/Android), microservices, cloud-native infra, real-time pipelines and API-first products. Drive hiring, retention, and engineering culture; integrate EPOS/payment systems; deliver AI/ML consumer features using LLMs, prompt engineering, and RAG. Champion AI tooling, DevOps best practices, and AI-augmented development workflows across the organisation.
Essential Experience
- 10+ years of software engineering experience, with at least 4-5 years in senior engineering leadership (Head of Engineering, VP Engineering, or Engineering Director).
- Proven track record of leading and scaling distributed engineering teams of 50+ engineers across multiple locations.
- Deep hands-on technical background in backend engineering, distributed systems, and mobile platforms (iOS/Android).
- Experience in a consumer-facing marketplace, e-commerce, food tech, or logistics platform at scale.
- Strong understanding of microservices architecture, cloud-native infrastructure, real-time data pipelines, and API-first design.
- Demonstrated success in hiring, developing, and retaining senior engineering talent.
- Strong commercial instinct — ability to balance engineering quality with speed to market.
Requirements
- Experience working in a challenger/scale-up environment
- Familiarity with EPOS/POS systems, payment gateway integrations, or restaurant technology.
- Experience leading offshore or near-shore engineering teams, particularly in India.
- Hands-on experience with AI/ML product features in consumer apps — recommendation engines, search ranking, dynamic pricing, and personalisation at scale.
- Practical experience integrating and shipping AI-powered features using LLMs (such as Claude, GPT, or Gemini), including prompt engineering, RAG pipelines, and responsible AI deployment in production environments.
- Familiarity with AI developer tooling and emerging standards such as Model Context Protocol (MCP), AI coding assistants (Claude Code, Cursor, GitHub Copilot), and agentic workflows — with the ability to champion their adoption across engineering teams.
- Track record of driving engineering culture transformation and introducing modern DevOps/engineering practices, including establishing AI-augmented development workflows as a core part of the engineering culture.
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