Senior Backend Engineer, ev.energy

• Our core platform is built in Python and Django, so we're looking for experienced backend software engineers with strong Python skills; Django experience would be beneficial but we’re open to other frameworks
• You'll be the person who takes a product idea and builds the systems, services, and infrastructure that make it real — reliable, scalable, and fast to iterate on. We're not looking for generalists who dabble across the stack — we're looking for someone with deep backend craft who can move fast, build with AI as a core part of how they work, and take genuine ownership of what they ship
• Strong Python experience (5+ years), with a clear track record of building and shipping production backend systems
• Experience building backend services with a Python framework (e.g Django, FastAPI or Flask)
• Strong experience building with AI — you've taken AI-powered features or products from concept through to production, and use AI coding tools (Claude, Cursor, or equivalent) as a genuine daily practice, not just occasionally
• Solid understanding of backend fundamentals — APIs, data modelling, databases, system design, and production reliability
• Experience leading technical decisions and influencing direction without relying on hierarchy
• Strong communication skills — written, verbal, and technical — credible with engineers, product, and commercial stakeholders
• High bias for action and comfort with ambiguity — you make good technical decisions with incomplete information
• Experience with Django
• Direct customer conversation experience that's shaped what you've built

Desirable

• We're hiring for a number of roles across both of our Technology teams: new product development and customer delivery. We'd love to talk to you about both teams, understand what excites you, and place you into the team where we think you'll thrive best
• Backend engineering and architecture
• Design, build, and own backend services and APIs that power our product — from data models to infrastructure to production reliability
• Make sound architectural decisions that balance shipping speed against long-term maintainability and scale
• Take ownership of significant technical areas — from identifying the right approach to shipping and iterating in production
• Building and shipping with AI
• Use AI coding tools (Claude, Cursor, or equivalent) as a core, daily part of how you write and ship code — not an occasional add-on
• Build working backend prototypes fast — good enough to validate with real usage, not over-engineered before it's proven
• Know when a rough implementation is right for the moment and when production-grade engineering is needed — and apply that judgment confidently
• Ship, measure, learn, iterate — kill what isn't working, double down on what is
• Product and stakeholder collaboration
• Work closely with product, design, and commercial stakeholders to translate customer problems into technical solutions
• Act as a credible engineering voice in cross-functional discussions, pilot programmes, and technical scoping conversations
• Partner with Customer Support, Program Management, and Demand Generation to understand how customers find, adopt, and stay with ev.energy
• Raising the bar
• Share what you learn openly, challenge how things are built, and raise the technical bar for the engineers around you
• Model what AI-native backend engineering looks like in practice — not in theory
• Contribute to a culture of experimentation, velocity, and commercial impact