Use AI responsibly to improve engineering

• Identify and apply AI-assisted engineering opportunities that create measurable value, including development, testing, documentation, defect investigation, and repetitive engineering tasks
• Define practical standards for the safe, secure, and responsible use of AI-generated outputs, with appropriate human review retained
• Embed AI-assisted development and testing into the software delivery lifecycle without lowering engineering quality
• Guide engineers in effective adoption, evaluate emerging tools pragmatically, and share what works

Solve the right problems

• Connect technology decisions directly to business value, customer outcomes, operational risk, and cost to serve
• Understand business, customer, operational, and financial drivers, then shape solution choices and product direction through technical insight
• Prioritise engineering investment according to impact rather than technical preference
• Establish performance baselines, service objectives, and capacity plans. Use trends and forecasting to anticipate demand, manage application health, and identify scaling risks before customers are affected

Grow capability

• Provide technical leadership across initiatives and teams, creating a coherent engineering vision and influencing decisions beyond the immediate squad
• Make clear, fact-based decisions in ambiguity, challenge assumptions constructively, and build consensus across engineers and stakeholders
• Balance short-term delivery with long-term sustainability and represent engineering in strategic discussions
• Identify emerging technologies and improvement opportunities pragmatically, translating worthwhile ideas into practical adoption and measurable outcomes
• Develop future technical leaders through structured coaching and mentoring. Create stretch opportunities, give actionable feedback, and promote knowledge sharing across the team

Your technical background

We are more interested in evidence of sound judgement and outcomes than a checklist of technologies. You should nevertheless bring strong, current engineering depth in most of the following areas:

• Strong commercial C# and modern.NET experience, with the ability to produce clean, idiomatic, and well-tested production code
• Production experience designing services-based or distributed architectures and defining service boundaries, data ownership, and communication patterns
• Hands-on Microsoft Azure experience, ideally including Azure SQL, Service Bus, Functions, Key Vault, container platforms, and monitoring services
• CI/CD and infrastructure-as-code experience using Azure DevOps or equivalent, with automated build, test, security, and deployment controls
• Strong knowledge of TDD, automated testing, secure engineering practices, observability, and operational support
• Experience with event-driven systems and relevant patterns such as idempotency, outbox, sagas, CQRS, or event sourcing where appropriate
• Practical use of AI-assisted software engineering tools while maintaining security, quality, and human accountability

Leadership experience

• Evidence of setting technical direction and leading complex cross-system design, not only delivering assigned components
• Ability to explain architectural trade-offs, risks, and assumptions clearly to both engineers and business stakeholders
• A track record of improving engineering standards, delivery flow, platform reliability, or operational performance using evidence and metrics
• Experience mentoring engineers, with visible examples of helping others improve judgement, independence, and technical capability
• Confidence working with product and business stakeholders to shape priorities and translate needs into sustainable technical outcomes
• A pragmatic leadership style that can protect long-term quality while knowing when a simpler solution is the right one

Highly desirable

• Experience modernising a mature monolith through incremental migration rather than a high-risk rewrite
• Experience with .NET Aspire, Bicep, or Terraform, OpenTelemetry, distributed tracing, structured logging, and API management
• Knowledge of feature-flag frameworks, progressive delivery, and controlled rollback strategies
• Experience improving performance, capacity planning, or service-level objectives for business-critical applications
• Relevant Microsoft Azure certification, although practical evidence matters more than certification alone

The person we are looking for

• You enjoy solving difficult engineering problems, but you start with the business outcome rather than the technology
• You take ownership from design through production support and use operational learning to improve the platform
• You communicate clearly, document decisions, and make complexity understandable
• You are evidence-led, comfortable making decisions in ambiguity, and willing to revisit them when context changes
• You get satisfaction from enabling others to succeed and measure leadership by the capability and outcomes of the wider team
• You combine ambition with pragmatism: raising standards without creating unnecessary process or perfectionism

Why join Evolve Energy?

You will have a meaningful voice in technology decisions and the opportunity to shape architecture, engineering practice, and team capability during a significant period of change. This is a hands-on technical leadership role with scope to leave a lasting impact on the platforms, the engineering culture, and the people around you.

How to apply

Please share your CV together with a short summary of a technical decision, engineering improvement, or mentoring outcome that best demonstrates how you enable a team to deliver better software.