Engineering Team Leader UK

Role Reporting to the Director of Engineering, the Engineering Team Lead is accountable for the leadership, technical direction, and end-to-end delivery of an engineering team responsible for key components of the StarCompliance Enterprise SaaS platform. This role combines strong technical leadership with people management and delivery accountability. Success is achieved through the capability and output of the team, while maintaining sufficient technical depth to guide design, challenge decisions, and support complex engineering work. You will own the full lifecycle of the software and services within your team’s domain, from design and development through deployment, operation, modernisation, and continuous improvement. StarCompliance is moving towards an AI-first, agentic software development model. You will lead this transition within your team, establishing ways of working where engineers and AI agents collaborate effectively across the software development lifecycle. How We Think About AI AI is a foundational part of modern software engineering at StarCompliance. We expect Engineering Team Leads to: Embed AI-assisted and agentic development into everyday engineering workflows. Enable appropriate engineering tasks to be safely delegated to AI agents. Ensure AI-generated changes are tested, validated, secure, and auditable. Use AI to improve delivery speed, quality, automation, and engineering capacity. Continuously adopt new AI capabilities where they provide measurable value. AI-generated output remains engineering output, and teams remain accountable for everything they deliver. Responsibilities Engineering Leadership & People Development Own the technical direction of systems and services within the team’s domain. Lead design decisions and ensure alignment with StarCompliance architecture and engineering standards. Maintain sufficient technical depth to challenge designs and resolve complex problems. Drive modernisation, simplification, and reduction of technical debt. Ensure scalability, security, resilience, performance, and maintainability are built in. Technical Leadership Own the technical direction of systems and services within the team’s domain. Lead design decisions and ensure alignment with StarCompliance architecture standards. Maintain sufficient technical depth to challenge designs and support complex problems. Drive modernisation, simplification, and reduction of technical debt. Ensure scalability, security, resilience, performance, and maintainability are built in. AI-First & Agentic Engineering Lead adoption of AI-assisted and agentic engineering practices. Structure work so engineers and agents can deliver effectively together. Increase the proportion of development activity that can be safely automated. Establish automated validation and guardrails for AI-generated changes. Measure AI adoption through improvements in throughput, quality, and engineering capacity. Delivery, Quality & Operations Own end-to-end delivery and ongoing health of the team’s products and services. Translate product priorities into clear and achievable engineering outcomes. Balance feature delivery with quality, resilience, security, and technical sustainability. Ensure software is tested, deployable, observable, supportable, and production-ready. Drive automation across testing, CI/CD, deployment, and operational processes. Use engineering and production data to improve quality and delivery effectiveness. Quality, CI/CD & Operational Excellence Ensure engineers own the quality of the software they create. Embed appropriate automated testing and quality controls throughout the SDLC. Drive high levels of CI/CD automation and low-risk, repeatable deployments. Ensure services provide effective telemetry, logging, monitoring, and alerting. Use production data and incidents to drive continuous engineering improvement. Platform & Collaboration Build solutions using modern Azure, cloud-native, and reusable platform capabilities. Partner with Platform Engineering, Architecture, Quality Engineering, Security, and Product. Work across team boundaries to resolve dependencies and systemic engineering issues. Communicate delivery, technical risks, and trade-offs clearly to stakeholders. Contribute to engineering-wide standards, forums, and improvement initiatives. Skills and Experience Significant software engineering experience, including technical and people leadership. Strong experience with C# and modern .NET / ASP.NET Core. Strong understanding of APIs, software architecture, and modern integration patterns. Strong experience with microservices, containers, and distributed systems. Experience with infrastructure as code and automated environment provisioning. Experience with event-driven architecture and asynchronous messaging. Experience building and operating enterprise SaaS or cloud-hosted applications. Experience with modern frontend technologies such as React and TypeScript. Strong knowledge of relational databases, particularly SQL Server. Practical experience with Microsoft Azure, CI/CD, automated testing, and modern engineering practices. Understanding of observability, resilience, performance, and secure software development. Practical experience using AI-assisted engineering tools and agentic development approaches. Experience supporting or leading AI-first or agentic engineering transformation. Proven ability to lead engineers, manage delivery, allocate resources, and influence across teams. Strong technical judgement, communication, coaching, and stakeholder-management skills. Minimum Qualifications Minimum Qualifications Degree in Computer Science, Software Engineering, or a related discipline, or equivalent professional experience. Experience within regulated SaaS or financial-services technology. Integrity and Ethics All StarCompliance employees are expected to commit to a high standard of personal integrity and carry out their responsibilities in an ethical manner. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.