Tech Lead (Lead Developer)
Indexed description
Purpose and Scope
Lead the design, delivery, and continuous improvement of secure, scalable full-stack applications, microservices, cloud-native solutions, and AI-enabled capabilities for Group Corporate digital initiatives. Guide a team of internal engineering team with primary delivery on Microsoft Azure while remaining adaptable to adjacent enterprise platforms, integration technologies, and evolving multi-platform solution needs.
Key Roles and Responsibilities
- Lead the end-to-end architecture, engineering, and delivery of full-stack applications and microservices-based solutions using .NET, JavaScript frameworks, Python, APIs, containers, and cloud-native Azure services.
- Define technical architecture standards, engineering guardrails, and solution design patterns to ensure quality, scalability, security, maintainability, resilience, and performance across enterprise platforms.
- Design, deploy, and optimise microservices architectures, including service decomposition, API integration, event-driven patterns, observability, and fault-tolerant distributed system practices.
- Lead and mentor software engineering teams, coordinate delivery plans, review code, and build technical capability across full-stack development, DevOps, and cloud engineering practices.
- Design, deploy, and optimise AI agents and intelligent workflow solutions integrated with enterprise applications, data platforms, and business processes.
- Build and maintain CI/CD pipelines, source control standards, release workflows, infrastructure automation, and environment management using Azure DevOps and related tooling.
- Collaborate with product, business, data, cybersecurity, and infrastructure stakeholders to translate business requirements into solution architectures, delivery roadmaps, and implementation plans.
- Integrate applications with Azure services such as messaging, data platforms, and analytics environments including Microsoft Fabric or Databricks where applicable.
- Oversee application lifecycle management, production support, incident resolution, technical risk mitigation, and continuous improvement of development, deployment, and operational practices.
- Contribute hands-on to software engineering tasks including backend services, frontend components, API development, automated testing, deployment automation, and technical documentation.
- Bachelor’s degree in computer science, Software Engineering, Information Technology, or a related discipline, or equivalent practical experience.
- Proven experience in a Tech Lead, Lead Developer, or Senior Full Stack Engineer role delivering enterprise-grade software solutions.
- Strong hands-on expertise in .NET and JavaScript-based full-stack development.
- Demonstrated experience designing, deploying, and supporting microservices architecture in enterprise or large-scale digital environments.
- Experience designing and deploying solutions on Microsoft Azure, including source repositories, CI/CD pipelines, integration services, and container-based deployment approaches.
- Experience deploying AI agents, intelligent automation, or applied AI solutions in production or near-production environments.
- Familiarity with enterprise data platforms such as Microsoft Fabric or Databricks.
- Working knowledge of Python for automation, AI integration, data processing, or backend services is an advantage.
- Demonstrated experience leading software engineering teams, conducting code reviews, and driving delivery outcomes across multiple workstreams.
- Strong understanding of software architecture, distributed systems, API design, cloud security, DevOps, testing strategy, observability, and operational support practices.
- Ability to engage cross-functional stakeholders, communicate technical concepts clearly, and balance strategic leadership with hands-on delivery.
- Industry-standard certifications are advantageous, including Microsoft Certified: Azure Developer Associate, Microsoft Certified: Azure Solutions Architect Expert, Microsoft Certified: Azure AI Engineer Associate, Azure Fundamentals, Kubernetes-related certifications, AWS Certified Machine Learning - Specialty, Google Professional Machine Learning Engineer, or comparable cloud, AI deployment, and solution architecture certifications.
- Strong written and spoken English proficiency is required to perform the role, including documentation, stakeholder communication, and collaboration across business and technical teams.
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