Optimal’s Mission

Optimal is building AI agents to control the world’s most critical infrastructure - from factories, to datacenters, and starting with high-tech greenhouses.

We are backed by the Director of AI Research at Google DeepMind, a Board Member at Meta, as well as early VCs in SpaceX, Anduril, and Palantir.

We have already built the world’s most advanced AI control for high-tech greenhouses and have proven breakthrough performance in customer greenhouses. We are actively scaling to more greenhouses and have signed integration partnerships allowing us to access 75% of the world’s greenhouses.

High-tech greenhouses are key to our agricultural future - for improving human nutrition and securing our food system against climate change and geopolitical instability. But the shortage of skilled operators causes existing greenhouses to underperform and prevents new greenhouses being built.

Our AI increases the profits of individual greenhouses by >$1M/year, increases yields, reduces energy and water usage, and unlocks global greenhouse expansion. There are 8,000 high-tech greenhouses in the world today giving Optimal an opportunity to create >8B/year of productivity gains. And by overcoming the shortage of skilled operators, we enable the rapid deployment of new greenhouses outside cities across the world.

Your Role

We are hiring a Founding Forward Deployed Engineer to own the bridge between our AI control system and real greenhouse operations.

We already have live deployments, integration partnerships, and strong early evidence that AI control can create very large value in commercial greenhouses. Now we need to scale from promising deployments to a repeatable system for onboarding, and delivering value to customers.

That is where this role comes in.

This role is part customer-facing engineer, part applied AI/controls engineer, part product builder.

What you will do:

• Speak with growers to understand their crops, greenhouses, and growing strategies.
• Adapt Optimal’s AI control to execute customer growing strategies automatically.
• Monitor production behaviour and identify where the system needs better tooling, guardrails, or product changes. Help to implement.
• Build internal tools, notebooks, agents, and workflows for onboarding, monitoring, intervention, and reporting.
• Find ways to add value to customers based on your direct customer interactions and observations. Work closely with other engineers in the company to deliver product improvements.
• Prototype grower-facing UIs that help customers control, understand and trust the system.

Your first 90 days:

• Visit a commercial high-tech greenhouse.
• Learn how growers think about climate, crop steering, risk, energy, and existing control systems.
• Help onboard a customer and translate their growing strategy into Optimal’s AI control system.
• Monitor production behaviour and identify where the system needs tooling, guardrails, or product changes. Help to implement.
• Build at least one tool or workflow that materially improves customer onboarding, monitoring, intervention, or reporting.
• Report performance to growers and gather feedback.

What are are looking for:

• Clear communication with technical and non-technical users.
• Strong intuition for physical and biological systems.
• Strong foundations in at least one of Machine Learning, Optimisation, Control (Model Predictive Control, Optimal Control, and classical feedback techniques), Reinforcement Learning, Physics Modelling and Numerical Simulation.
• Experience building useful tools quickly using AI agents/workflows, notebooks, code, operational playbooks.
• AI-native coding.
• Software engineering in Python.
• Software engineering processes and tools (containers, version control, deployments etc).

Why join

Optimal is early enough that the first few engineers will shape the product, culture, and deployment model.

As the founding FDE, you will help create the function from scratch and own the loop from customer need to production AI system to measurable customer value.

If we succeed, this role can grow into leadership of forward deployed engineering, customer engineering, deployment operations, or applied product engineering.