Senior Software Architect

TeamViewer

London, United Kingdom

Responsibilities

As a Senior Software Architect at TeamViewer, you will shape the architectural direction of scalable, secure, and high-performing software solutions that support our strategic goals. This is a hands-on architecture role requiring strong engineering judgement, technical credibility, and the ability to guide teams through complex design and delivery challenges. You will work closely with engineering, product, and operations teams to make pragmatic architectural decisions, improve system quality, and support long-term maintainability. You will also bring an AI-aware and forward-looking mindset, recognizing where modern AI capabilities, automation, and agentic workflows can improve product capability, developer productivity, operational efficiency, and customer value.

Your primary responsibilities will include:

Hands-On Architecture: Actively contribute to the design and development of enterprise-grade software solutions that are scalable, secure, cost-effective, and maintainable;
Implementation Support: Work closely with development teams, offering practical, hands-on guidance throughout the full software lifecycle - from concept to deployment;
Architectural Strategy: Define and evolve software architecture strategies that align with business goals, product direction, and engineering standards;
Concept and Design Reviews: Conduct detailed reviews of architectural concepts, providing feedback and suggestions to enhance design quality and system performance;
Technical Guidance: Lead technical discussions, mentor senior engineers and architects, and provide practical advice on complex technical challenges;
AI-Aware Architecture and Engineering: Apply strong architectural judgement while recognising where AI, automation, agents, and intelligent workflows can pragmatically improve product capability, developer productivity, operational efficiency, and customer value;
AI-Enabled Developer Productivity: Use and promote AI-assisted engineering tools such as GitHub Copilot, Cursor, Claude Code, or comparable tools to improve development workflows, code quality, refactoring, testing, and team effectiveness;
Practical AI Engineering Awareness: Stay current with relevant AI engineering practices, including concepts such as context windows, custom instructions, agentic workflows, tool use, prompt strategies, model selection, and safe enterprise adoption;
Cross-Functional Collaboration: Work closely with engineering, product, operations, and support teams to ensure architectural alignment and successful delivery across relevant product and platform areas;
Documentation: Create and maintain comprehensive architectural documentation that is clear, concise, and accessible to all relevant stakeholders;
Continuous Learning: Stay updated on industry trends and emerging technologies, applying this knowledge to enhance our software architecture;
Risk Management: Identify and document potential risks in the architecture, providing strategies to mitigate them effectively.

Requirements

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field;
10+ years of software engineering experience, including significant experience designing and evolving complex software architectures across multiple domains;
Proven ability to deliver hands-on, real-world solutions, actively supporting implementation, troubleshooting, and technical decision-making;
Strong understanding of designing enterprise-grade systems that are scalable, secure, cost-conscious, and maintainable;
Strong expertise in at least one modern back-end programming language, such as C#, Java, or C++, with the ability and willingness to learn new technologies as needed;
Solid experience with data systems, including SQL and NoSQL databases, data modelling, performance considerations, and operational behaviour at scale;
Practical awareness of how modern AI capabilities can be applied in software engineering and product architecture, while remaining anchored in maintainability, security, scalability, and business value;
Regular hands-on use of AI-assisted engineering tools such as GitHub Copilot, Cursor, Claude Code, or comparable tools, with an understanding of how to use them effectively in real engineering workflows;
Strong communication skills, with the ability to explain complex architectural concepts clearly to both technical and non-technical stakeholders;
Strong understanding of distributed systems, multi-platform development, non-functional requirements, and requirements engineering;
Ability to document complex technical systems and concepts in a structured, accessible, and standardized manner;
A pragmatic, outcome-focused mindset that balances technical excellence with business needs and delivery timelines.