Executive recruitment company Monroe Consulting Group's Technology division is recruiting on behalf of a highly established company with a robust footprint in the consumer, logistics, and technology sectors.
Job Summary: Our client is recognized for driving transformative initiatives, embracing innovation, and delivering long-term value to stakeholders. They are seeking a transformational Head of Architecture & Engineering to serve as the most senior technical leader driving their transition into a Digital/AI/Data-First services company. This pivotal leadership role will be instrumental in shaping the technological future of their services provided and will be accountable for building a scalable, intelligent, event-driven data platform that integrates AI into the core fabric of the business' operations. The ideal candidate will be blend of a strategic leader responsible for driving operational excellence in the current mission-critical and core systems at the same time architecting and delivering the next generation of digital platforms, leveraging cloud-native technologies, data analytics, and Artificial Intelligence (AI) to realize our digital ambition.
Job Responsibilities:
Enterprise Architecture (EA) & Digital Strategy - Define and govern the target state EA blueprint, specifically focusing on a composable business architecture where services are decoupled, autonomous, and API-driven. Define and champion the long-term technical roadmap, moving the business towards a modern, scalable, and resilient cloud-native microservices architecture. Lead the effort to integrate Generative AI and Machine Learning (ML) capabilities into core operations (e.g., predictive logistics, automated sorting, customer service bots, etc) to unlock new levels of efficiency, customer experience and revenue sources. Evaluate, recommend, and govern the adoption of new technologies, frameworks, and tools, ensuring alignment with business strategy and financial prudence. Actively mentor Solutions Architects, ensuring all solution designs are cloud-native, scalable, secure (DevSecOps), and utilize modern software patterns (e.g., Circuit Breakers, Saga Orchestration, etc) and best practises.
Software Engineering Delivery Excellence - Instill a laser focus on software quality, such as TDD, BDD, formal code review practices, and comprehensive unit/integration/end-to-end testing, minimizing production defects and system downtime. Drive the adoption of Agile methodologies (Scrum/Kanban) and lean development principles across all projects to maximize speed and responsiveness. Ensure all software development adheres to stringent security standards and regulatory compliance (e.g., data privacy, financial regulations), integrating security practices early in the development lifecycle. Implement best-in-class DevOps practices, including Continuous Integration/Continuous Deployment (CI/CD), infrastructure-as-code, and automated monitoring, to achieve rapid, high-quality software delivery. Bring thought leadership and industry best practises into the team. Oversee the automation of the entire CI/CD lifecycle, driving toward a goal of zero-touch deployment and automated releases. Ensure teams utilize the most effective modern language stacks and database technologies appropriate for the high-volume nature of the logistics domain. Demand and manage a unified Observability Platform (using distributed tracing, comprehensive metrics, and structured logging) that provides engineering teams with the necessary insights to proactively debug and optimize production systems. Strategically plan and execute programs to reduce technical debt in legacy systems through progressive modernization and refactoring, balancing innovation with stability.
AI & Data-First Engineering - Own the design, implementation, and governance of the end-to-end MLOps platform, ensuring automated, secure, and reproducible pipelines for model training, deployment, monitoring, and experimentation. Direct the technical integration of Generative AI and Predictive ML Models into mission-critical production systems. Guide the architectural shift towards a Data Mesh model, where data is treated as a product, owned by domain teams, and readily available as standardized, quality-assured data products for consumption across the Group. Architect cloud-native solutions for the storage, processing, and analysis of large volumes of unstructured data (e.g., images, sensor data) critical for advanced logistics and computer vision applications.
Engineering Leadership & Talent Development - Be a magnetic force for top-tier engineering talent, specializing in building and upskilling teams in Cloud, AI, and Distributed Systems. Foster a culture of technical curiosity, transparency, and blameless post-mortems. Lead, mentor, and grow a high-performing software engineering team across various disciplines (Backend, Frontend, Data Engineering, QA, and DevOps). Cultivate a transparent, data-driven, and innovative engineering culture focused on quality, agility, and continuous improvement. Partner closely with the various Business Units and Digital teams (Product Management, Data Science, Operations & Security) to ensure technical solutions align with market needs and business objectives. Effectively manage the software engineering budget, resource allocation and vendor relationships to ensure efficient delivery.
Key Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field - Or equivalent practical technical experience.
Minimum of 12+ years of progressive experience - In software development and architecture, with at least 5 years in a senior leadership role (e.g., Chief Architect, Head of Engineering, VP of Technology, or similar).
Experience in managing teams of 50+ engineers
Demonstrated experience in a highly transactional, high-scale digital environment - E.g., E-commerce, Logistics, FinTech.
Proven track record - In driving large-scale digital transformation or modernization projects in a highly transactional, high-scale digital environment preferably within the logistics, e-commerce, or financial services industries.
Deep expertise in cloud computing platforms - AWS/Azure and experience migrating complex systems to the cloud.
Expertise in designing and building scalable systems - Using modern stacks (e.g., Python, Go, Node.js, Java) and technologies (e.g., Kubernetes, Kafka, Serverless functions).
Strong understanding & track record - Of Data Engineering pipelines, ML model deployment, and MLOps.
Fluency in architectural patterns - Microservices, Event-Driven Architecture and best practices for system security and resilience.
