Staff Product Manager - Rosso (Portfolio)

About tem

We are rebuilding the energy transaction, making it transparent and fair. We cut out middlemen, connect businesses directly with renewable generators, and ensure every transaction is traceable and transparent.

We are a 160+ person team—operators, data scientists, engineers, customer champions, and energy experts—backed by top-tier investors including Lightspeed Venture Partners, Hitachi Ventures, Allianz, AlbionVC, and Atomico. We closed a $75M Series B round in early 2026, taking our total funding to $94M, and we now power energy for over 4,000 UK businesses across 8,500+ sites, with over £75m in value returned to businesses and generators so far.

We are a technology company solving the energy industry, not an energy company. Some people call us a neo-utility—the neo-bank idea applied to energy.

The Role

We’re hiring a Staff Product Manager to own the portfolio side of Rosso, a hands-on role built around financial outcomes.

Rosso is deeply technical, built on ML-led models and complex engineering covering forecasting, pricing optimisation, and portfolio balancing. The portfolio is where the live financial risk sits: fulfilling and balancing a growing two-sided portfolio, managing imbalance, controlling portfolio costs, and finding the revenue and margin in every position we hold.

This is a lead role, but not a head-of-product role. You’ll be building, not running a product practice. You’ll work day to day with engineers and ML specialists to build an automated portfolio management system that handles balancing, forecasting, and counterparty placement, which could be exposed to third parties in the future.

Responsibilities

Own the Portfolio Outcome

• Take full ownership of financial outcomes in the portfolio area: balancing, imbalance, forecasting, and counterparty placement.
• Treat hedging, imbalance, and trading decisions as product decisions: when to hold a position, when to trade it out, when to reprice to close a gap.
• Find the most pressing problems worth solving, such as whether to buy or build a new forecasting capability, or how to make Rosso react at scale to any event in the system.
• Chase the commercial outcome, not just the shipped feature. The measure of this role is margin found and risk managed, at pace.

Turn Needs into Shipped Product

• Take business and customer needs and turn them into feasible product execution, balancing them against nascent ML and forecasting innovations that push the frontier of what’s possible.
• Take initiatives from discovery through to regularly released product.
• Drive open product decisions to a close so work keeps moving.
• Decide what to formalise, what stays a prototype, and what to drop. Be the editor and builder, not just the instigator.

Own the Technical-Product Detail

• Work embedded in full-stack teams of ML/data science and software engineers, close enough to the systems to make good calls.
• Set clear success criteria for model and forecast performance, designing for edge cases and live financial risk realities.
• Interrogate data to inform decisions and reason about model performance and error as business indicators.
• Get close to internal commercial teams as well as external generators and businesses.

Lead by Doing

• Set the pace for the product team and raise the standard of product work around you through your own work and example.
• Work alongside the other PM on Rosso and the Product Lead, with clear ownership of the portfolio area.

Requirements

Must Haves

• Senior, hands-on product management experience (hiring at L4, considering L5 for exceptional candidates). Proven track record owning a complex, financially significant product end to end and driving real business outcomes.
• Domain knowledge in energy trading and markets: positions, hedging, balancing, imbalance, and live financial risk systems. Strong adjacent experience (financial trading, fintech, battery/EV trading) considered with demonstrated depth of understanding.
• Experience building automated, quantitative systems or working closely in engineering pods that do.
• Strong commercial drive to push decisions to a close and capture revenue and margin.
• Comfortable working alongside ML specialists and data scientists, reasoning about model performance and error as business metrics.
• Data-driven approach throughout discovery, execution, and post-launch measurement.
• Background in a startup, scaleup, or high-growth environment with strong personal ownership.
• Strong instinct for failure points, edge cases, and operational realities of live systems.
• AI-native, AI-literate, and AI-critical.
• Clear, structured communicator, particularly in writing.

Nice to Haves

• Hands-on energy trading experience: intraday, day-ahead, imbalance, or battery optimisation.
• Experience where forecasting or fulfilling a two-sided marketplace is central to the product.
• Experience navigating third-party-access or international-expansion transitions.
• Experience with regulated industries and data-heavy products.

Benefits & Perks

• Competitive Salary: Base pay band for this role is £127,728 (or equivalent local currency).
• Stock Options: Equity ownership in our mission for every team member.
• Time Off: 25 days holiday + public holidays (with flexibility to swap public holidays), plus an extra day off for your birthday.
• Remote & Flexible Working: Fully remote across Europe with clear core hours and no internal meetings on Friday afternoons.
• Home Working Budget: Up to £1,200 / €1,200 annually for remote setup upgrades (co-working passes, equipment, etc.).
• Wellbeing Budget: Up to £150 / €150 monthly for wellbeing resources (therapy, gym memberships, meditation apps, etc.).

Interview Process

Our process typically takes 2–3 weeks:

1. Talent Team Intro (30 mins): Experience, motivations, and role overview.
2. Behavioural Interview with General Manager (30 mins): Deep dive into role expectations and alignment on ways of working.
3. Technical Scenario Interview (75 mins): Discussion on product execution, ML collaboration, and real model-driven product decisions.
4. Bar Raiser Interview (30 mins): Cross-functional chat focused on values alignment and mutual fit.