Lead Software Engineer (Hybrid)

Our client is a software consultancy. Lead Engineer Location : Waterloo, London, England, UK | Hybrid (1 day per week in office) Who We Are We bring life to the best ideas. Founded in 2006 and headquartered in Chicago, we are a technology solutions consultancy that partners with organisations from early-stage startups to the world's largest companies.

We take on hard software challenges and turn them into durable results. We build agentic products, the platforms they run on, and the engineering and design at every layer. Our commitment to quality means we deliver solutions we're truly proud of, while our curiosity sparks innovation and breakthrough thinking.

8th Lights thrive in an environment that champions continuous education, fueling our growth through mentorship and hands-on work. We foster an open, collaborative culture grounded in honesty that builds trust, and believe true success is measured by the outcomes we create for our clients.

If this kind of work and our kind of people energises you, you've found the right place. Who You Are You've shown long-term repeated success on a variety of projects, typically over the course of 7+ years. You can be the go-to leader for any software development engagement.

You have a broad and deep range of expertise that allows you to make an immediate impact on projects. In your previous experience, you have: Successfully led high-stakes consulting engagements from discovery to production Built high-quality, maintainable software collaboratively, incrementally, and through an approach tailored towards the unique needs of the clients you've served Written production-quality code using a variety of languages and frameworks, including but not limited to: Java, C#/.NET, Python, TypeScript, JavaScript, React, Go, Ruby, Scala, R, and SQL Leveraged AI-assistive development tools for tasks like scaffolding, refactoring, debugging, test generation, and documentation Experience building or integrating AI/ML-powered features into products or systems (e.g., recommendation engines, NLP models, computer vision, predictive analytics) Used context-appropriate automated testing to inform software design choices and catch bugs Debugged and refactored pre-existing code to incrementally improve it

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