Tem is a London-based AI energy marketplace and neo-utility that matches renewable electricity generators with business consumers to lower power costs.
📈 Who We Are: We are rebuilding the energy transaction, making it transparent and fair. Our goal is to put power back where it belongs, in the hands of customers and to take on one of the most critical problems of our century, access to low cost electricity. tem exists to fix a broken global energy market that’s long favoured legacy operators, intermediaries, and opaque pricing. Today’s electricity system was not designed for rapid decarbonisation, AI-driven efficiency or fair access for the actual users - businesses and generators. We’ve built the first AI native transaction infrastructure to reinvent how electricity is bought, sold and priced. Our technology is designed to cut out the inefficient fees, automate complex market flows, and bring transparency and fairness to energy transactions at scale. In late 2025, after extraordinary growth, we closed a $75 million Series B - led by Lightspeed Venture Partners with participation from Albion, Atomico, Allianz, Hitachi Ventures, Hitachi Ventures, Schroders Capital and others - positioning us for global expansion, deeper product innovation and category leadership. We’re scaling internationally and building toward a future where AI-driven infrastructure is foundational to electricity markets worldwide. Since launch, our modern utility product, known as RED, has already facilitated thousands of business customers and billions in energy transaction value, proving that modern software and AI can transform an industry built on legacy systems. At tem, we’re not just building another energy company, we’re rearchitecting market infrastructure so that transparency, efficiency and sustainability become the default, not the exception. 🏅 THE ROLE: Rosso is tem's core pricing infrastructure. It brings together forecasting, margin optimisation, and portfolio balancing to price energy tenders from first input through to signed contract — and keeps the portfolio healthy as we grow. It sits directly on the critical path for revenue. This is a rare role. We're looking for someone who combines Principal-level distributed systems depth with real, hands-on experience bringing ML models into production — and who does all of it in Python. That combination is genuinely uncommon, and we know it. You'll own the most complex technical deliveries in Rosso end-to-end: designing the system, writing the code, partnering with our Data Science and ML teams to get pricing and forecasting models running reliably in production, and setting the technical direction for how Rosso scales. You'll challenge the brief, commit to a direction under uncertainty, and be accountable for outcomes — not workstreams. If you've spent your career at the intersection of high-stakes backend systems and ML productionisation, and your instinct when given a hard problem is to get into it rather than frame it, this role was written for you. 🚀 RESPONSIBILITIES: - Own Rosso's most complex deliveries. Lead high-impact improvements across pricing and deal-flow workflows — improving correctness, operability, and scalability as volume grows. You drive these from first design through to production. - Bridge ML and production infrastructure. This is the heart of the role. Work directly with our Data Science and ML teams to bring forecasting, optimisation, and pricing models into Rosso's core workflows safely, correctly, and at scale. You'll co-own the design of how models integrate with production systems — not just the infrastructure wrapper around them. - Make architectural decisions that last. Design and evolve a stateful, event-driven Python system where business logic is the primary source of complexity. Set clear domain boundaries and prevent the drift that compounds over time. - Lead across teams. Drive cross-functional initiatives spanning engineering, product, data, ML, and commercial stakeholders. Align people around a technical direction and deliver. - Raise the bar. Mentor Staff and Senior Engineers, drive observability and testing standards, and act as a trusted technical voice to engineering leadership. - Plan for scale. Architect for high-volume quoting activity and large customer counts — anticipating bottlenecks before they surface in production. 🎯 REQUIREMENTS: Must-Haves: - You are a Python expert. Not just comfortable in Python — you have deep expertise in building and operating production Python systems at scale. You know the language's performance characteristics, packaging and dependency patterns, async and concurrency models, and you have opinions about how to build Python systems well. - You have genuine ML productionisation experience. You've worked at the boundary of ML and backend engineering — integrating models (forecasting, optimisation, pricing, or similar) into production systems, designing the infrastructure around them, and owning what happens when they fail or drift. This isn't coordination experience; it's hands-on engineering. - You operate at Principal level with organisation-wide impact. You've owned major technical initiatives at a high-growth startup and can point to what changed because of it. Not just influence — shipped outcomes with measurable business impact. - You have deep application architecture depth in complex domains. You've designed and evolved stateful distributed systems — APIs, event-driven architectures, data pipelines — where domain logic is the hard part. You know what domain drift looks like and how to prevent it. - You're strong with AWS serverless architecture. Hands-on experience with Lambda, API Gateway, DynamoDB, and event-driven, asynchronous workflows — operated in production and learned from failure. - You can drive to a concrete decision under ambiguity. You ask sharp questions to narrow the problem space, commit to a direction, and take responsibility for the outcome. You don't narrate a methodology — you execute one. - You connect technical decisions to business outcomes. Techni