Founding leadership opportunity

Head of Insurance

Equity-only · Unfunded · Flexible commitment

No salary or fee budget is available. Equity, scope, commitment and engagement terms must be agreed before work begins. Future cash compensation is not guaranteed.

About Optimising Technologies

Optimising Technologies is a young robotics company founded by Mark Marney. We are building software to help robotics teams understand regulatory requirements, record how their robots operate and prepare information that insurers can use. You can try the NOMOS prototype today. Sentinel is in development, and Ledger is at the research and validation stage. You will work directly with Mark, our founder and CEO, to turn these early products into tools customers can use.

The opportunity

Build the insurance proposition for a new generation of robotics deployments. You will turn an emerging technical capability into a product and operating plan that insurers, brokers and customers can evaluate. This is a hands-on role for someone who has taken commercial insurance products or underwriting propositions from concept into practical market engagement.

Reporting to Mark Marney, you will work with the technical and regulation leads to identify which evidence helps with risk selection, pricing, policy terms and claims. You will own insurance strategy and delivery, with actuarial and legal specialists supporting work requiring their expertise.

What you will own

• Define the initial customer segment, insured activities, use cases and distribution route. Build a clear value proposition and establish where coverage, exclusions or evidence requirements create a customer problem.
• Develop a carrier-ready underwriting business plan: risk appetite, exposure measures, limits, deductibles, aggregation, expected loss assumptions, expenses, acquisition costs and premium scenarios.
• Lead carrier, broker and specialist market discussions. Establish what evidence and operating capability they require before offering support; record commitments and unresolved conditions accurately.
• Work with an appropriately experienced actuary on pricing and portfolio scenarios. Separate measured evidence from assumptions and simulation; make uncertainty visible.
• Develop product and wording requirements, claims and incident processes, delegated-authority controls and management information with relevant specialists and potential partners.
• Evaluate the practical insurance operating route with qualified advisers. Coordinate the permissions, governance and outsourcing work that route requires before regulated activity begins.
• Specify useful underwriting and claims outputs for Ledger and Sentinel. Help the team prioritise features that solve a real insurance decision, then build the insurance team and budget as traction grows.

Your first 90 days

We will agree the scope around your available time and commitment.

Days 1–30: agree the target segment, customer problem, operating-route options and key assumptions; produce a structured carrier discussion pack.

Days 31–60: test the proposition with relevant market participants; complete a first underwriting economics model and product requirements with specialist input.

Days 61–90: deliver a revised business plan, documented market feedback, pilot evidence requirements and a costed route to the next commercial milestone. Carrier support is an objective, not a guaranteed outcome.

Essential experience

• Personal ownership of commercial insurance underwriting, product development or an MGA proposition, including credible examples of moving from design to market delivery.
• A practical grasp of risk appetite, pricing drivers, wording, portfolio economics, distribution and claims. You can explain the assumptions behind a viable product.
• Experience working directly with insurers, capacity providers or delegated-authority partners and navigating their diligence requirements.
• Ability to translate incomplete technical and customer evidence into clear underwriting questions, while recognising when an actuary, lawyer or specialist must decide.
• Comfort building the plan and producing the work yourself in a small company, alongside a founder and engineers. Strong written communication and commercial judgement.

Useful, but not required

Experience in robotics, industrial technology, product liability, engineering, cyber or other emerging risks; Lloyd’s or London-market relationships; an insurance qualification; experience of a new venture. Direct robotics experience is helpful, but strong relevant insurance delivery is more important.

Scope and support

You own insurance product and market development. The regulation lead owns robotics assurance methodology; the technical lead owns software delivery. Pricing validation, legal advice and specialist compliance work will use appropriate expertise. This role does not carry an assumed authority to bind insurance or promise capacity.

Working arrangements and reward

Help build the company and the team from the start. We are looking for people who have delivered work they are proud of and want to take on a founding role. We welcome fractional involvement and will agree a realistic workload and time commitment together.

Optimising Technologies currently has no funding. This opportunity is equity-only at this stage: there is no salary or fee budget. We are open to fractional engagement and other mutually agreed arrangements. Equity percentage, vesting, responsibilities and time commitment will be agreed in writing before work begins. Future cash compensation depends on funding and a separate agreement; it is not guaranteed.

How to apply

Provide your CV and a cover letter answering the questions below, up to 400 words in total. Include your location, availability, preferred commitment and proposed engagement terms. Please avoid confidential material from another employer or client.

• Describe one insurance product or underwriting proposition you personally helped bring to market. What did you own and what happened?
• Give an example of securing or progressing carrier/capacity support. What evidence changed the decision?
• For a new robotics insurance proposition, what would you need to know before recommending risk appetite or pricing?