VP - Engineering

Responsibilities:

• Define and drive the technology vision, architecture, and long-term platform roadmap.
• Oversee the architecture, design, and delivery of highly scalable enterprise systems.
• Ensure engineering excellence, velocity, and reliability across the product lifecycle.
• Lead platform engineering, product technology, DevOps, infrastructure, and Quality Engineering.
• Build robust cloud-native systems using Azure, AWS, and GCP ecosystems.
• Oversee operational effectiveness, including uptime, production reliability, and cost optimisation.
• Spearhead Mission AI by developing scalable and production-grade AI/ML and GenAI capabilities.
• Own the GenAI/LLM Solutions Architecture.
• Core specialisation in AI Agents and Autonomous workflows, Data Extraction and Intelligent Automation.
• Direct hands-on architectural oversight of Large Language Models (LLMs), Applied AI, and multi-layered deep learning products.
• Extensive expertise in building intelligent document automation systems (similar complexity to patent parsing, legal workflow automation, and structured decision intelligence tools).
• Proven track record overseeing product architecture, tech strategy, and cross-functional engineering execution across core full-stack and AI platforms.
• Collaborate with Executive Leadership on business strategy, client requirements, and product delivery.
• Build, mentor, and scale high-performing engineering teams with a growth mindset.
• Establish a strong technology culture grounded in ownership, innovation, and continuous learning.
• Mission AI: Build a world-class AI system leveraging GenAI, ML, and enterprise-grade data engineering.
• Hyper-Scaling: Architect and scale our platform to match global industry leaders in the IP space.
• Culture Building: Develop a strong engineering organisation with high ownership, performance, and innovation DNA.

Requirements:

• 0-15 years of enterprise software engineering experience across B2B SaaS or technology-first companies.
• Proven track record of taking early-stage AI/ML prototypes and scaling them into robust enterprise SaaS platforms featuring multi-agent orchestration, complex workflows, and decision intelligence.
• Experienced in building and mentoring agile, lean startup teams comprising Full Stack and Machine Learning engineers from the ground up.
• Proven leadership in defining and executing technology strategy and platform roadmaps.
• Extensive cloud-native engineering experience with Azure, AWS, and GCP.
• Strong full-stack engineering background (Java, Python, JavaScript frameworks).
• Expertise with JS frameworks such as React, Angular, Node.js .
• Experience building and scaling distributed systems and microservices.
• Strong knowledge of databases (SQL, NoSQL), data modelling, and unstructured data management.
• Strong understanding of Agile methodologies and tools (Atlassian, Git, CI/CD pipelines).
• Product and Delivery management expertise (end-to-end, including delivery and customer support).
• Excellent communication skills with the ability to influence executive stakeholders.
• High technical proficiency combined with strong business acumen.
• Strong analytical and decision-making skills.