About the company
For more than 18 years, Qubiz has been a leading tech company with 350+ employees.
By prioritising people, both colleagues and clients, we have created an environment focused on well-being, which allows us to deliver exceptional performance.
Most importantly, our retention rate has consistently remained around 90%, and many of our colleagues have been with us for 5, 10 or even 15 years — a strong testament to the long and successful careers people can build with us.
About the role
We are looking for a Senior .NET Tech Lead who combines strong hands-on engineering with product thinking, client-facing confidence, and an AI-first approach to software delivery.
You will work closely with clients, product stakeholders, and multidisciplinary teams to understand business needs, shape solutions, and lead delivery from discovery through production. You will create direction when requirements are incomplete or priorities change, making pragmatic decisions that balance business value, speed, quality, security, cost, and maintainability.
You will take ownership of evolving the team’s engineering approach around AI. This includes identifying opportunities, adapting delivery workflows, leading adoption, and assessing whether changes improve outcomes. You will apply judgement to decide where AI adds value, establish appropriate validation, protect client information, and remain accountable for the final solution.
What you will do
- Lead the technical direction and delivery of .NET solutions, from discovery and architecture through implementation, release, and continuous improvement.
- Work directly with clients and product stakeholders to understand their objectives, challenge assumptions constructively, and define what success looks like.
- Translate business challenges into technical options and recommendations, explaining trade-offs, risks, dependencies, and costs.
- Stay hands-on with implementation, code review, debugging, and production troubleshooting, particularly where complexity or risk requires your involvement.
- Guide the team in breaking down complex problems and delivering incremental, testable outcomes.
- Evolve the engineering approach around AI: actively identify opportunities for AI-assisted delivery, challenge established practices, and adapt workflows where needed. Apply judgement to decide where AI adds value and where it introduces unnecessary complexity or unreliable results.
- Integrate AI into analysis, design, implementation, testing, review, debugging, and documentation. Provide the context and instructions needed to guide AI-assisted work, and validate the results.
- Lead AI adoption across the team: experiment with approaches, share effective practices, coach colleagues, and address barriers to effective use.
- Establish team practices for responsible AI use, including human review, testing, approved tools, appropriate access permissions, and protection of client data.
- Maintain sound delivery practices across automated testing, CI/CD, security, observability, reliability, and production readiness.
- Own continuous improvement: assess the impact on the whole delivery process, including delivery speed, review effort, rework, defects, and cost, and adjust practices based on evidence.
- Mentor engineers and build a collaborative environment that encourages ownership, constructive challenge, continuous learning, and growing autonomy.
Requirements
- Extensive software engineering experience, with strong expertise in .NET and C# and the technical depth to design, implement, and lead complex solutions.
- Strong knowledge of software architecture, maintainable code, APIs, integrations, databases, automated testing, and security.
- Experience delivering and supporting production systems, including CI/CD, observability, reliability, and operational troubleshooting.
- Experience making architectural decisions and clearly explaining the assumptions, alternatives, risks, and trade-offs behind them.
- Experience leading technical delivery and mentoring engineers while creating direction and ownership without micromanagement.
- Strong client-facing communication and facilitation skills, with the confidence to build trust, manage expectations, and challenge assumptions constructively.
- A consultancy and product mindset: understanding the business context, identifying the real problem, proposing options, and focusing on outcomes.
- Practical experience using AI coding assistants or agents in software delivery, including providing context, defining tasks, reviewing changes, and validating results.
- The ability to lead AI adoption, challenge and adapt engineering workflows, and evaluate their impact while maintaining accountability for quality, security, and maintainability.
- The autonomy and judgement to work effectively in ambiguous situations, knowing when to investigate, decide, involve others, or escalate.
- Strong ownership, curiosity, and willingness to adapt as technologies and engineering practices evolve.
- Business-level English proficiency, written and spoken.
Nice-to-have
- Experience supporting pre-sales activities, technical proposals, solution estimations, or technical due diligence.
- Experience with Azure or other cloud platforms.
- Experience integrating AI capabilities into products, including model integration, output evaluation, and production monitoring.
- Experience configuring AI coding workflows, repository instructions, or tool integrations.
- Relevant Microsoft, cloud, architecture, security, or AI certifications.
What is in it for you?
- Real responsibilities and challenging projects
- Friendly environment
- Clear career paths and mentorship opportunities
- Training and certifications to boost your skills
- Additional annual leave days based on seniority
- Private health insurance
- Company events
- Discount for gym or sports pass of your choice
- Discount for prescription glasses
- Meal vouchers