SVP of Engineering
We're looking for an SVP of Engineering to scale our AI-powered platform and deliver products that protect millions of customers worldwide.
You'll lead our global engineering and data science organization as we build the future of insurance, where cutting-edge AI meets human-centered design. This role sits on our executive team and reports directly to our Chief Product Officer, driving technology decisions that create real customer value.
We believe two things matter for every leadership role at Lemonade: leadership that sets the bar for excellence, builds high performing teams, and holds them accountable, and strategy that thinks several years ahead and turns ambitious plans into reality. These aren't buzzwords, they're how we actually work.
In this role you'll
Build and execute a technology strategy that turns vision into scalable, secure platforms customers love
Lead and mentor senior engineering leaders while fostering a culture where speed meets quality
Translate product roadmaps into multi-year engineering plans that balance innovation, reliability, and cost
Oversee complex delivery across software, data, AI/ML, and infrastructure — always with product outcomes in mind
Drive talent strategy for engineering teams, from hiring plans to performance management and retention
Represent engineering in executive discussions, communicating progress and trade-offs to drive smart decisions
What you'll need
Adaptability, drive, and an efficiency mindset - we believe these matter most in human-AI collaboration
15+ years in engineering leadership, including executive experience running large engineering functions
Track record delivering large-scale, multi-product platforms with measurable business impact
Deep expertise in software architecture, data systems, AI/ML workflows, security, and reliability
Strong people leadership and executive presence with proven cross-functional collaboration skills
Experience with modern engineering practices: Agile/Lean, CI/CD, cloud ecosystems, observability
Data-driven approach to decision making with focus on quantified outcomes and customer value
Educational degree in Computer Science, Engineering, or related field (or equivalent experience)
Ready to work in an office environment most days of the week