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.