Founding leadership opportunity

Head of Regulation

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 regulatory and assurance capability behind our products. You will translate requirements affecting robotics and AI-enabled systems into practical evidence workflows that engineers, operators and reviewers can use. The role centres on robotics product assurance and real deployment evidence; it requires more than general policy knowledge.

Reporting to Mark Marney, you will work with the technical and insurance leads to define what can be evidenced, what needs expert judgement and where the limits of the software must remain explicit. You will own the methodology and content quality behind NOMOS and the assurance requirements that connect to Sentinel.

What you will own

• Map the applicable requirements for the initial robot, deployment context and target market. Maintain a traceable, version-controlled requirements register and document assumptions, applicability and unresolved interpretation.
• Translate requirements into evidence requests, review criteria and customer workflows. Distinguish supplier documentation, operating records, test results and independent assessment.
• Design the NOMOS assurance approach: evidence completeness, provenance, review status, exceptions, change control and clear human sign-off. Define where automated assistance is appropriate and where expert review is essential.
• Work with engineers and appropriate safety specialists to connect hazards, intended use, operating limits and fault scenarios to testable evidence requirements.
• Work with the insurance lead to make evidence useful to underwriting and claims without overstating what compliance or a test result proves about loss risk.
• Build relationships with relevant assessors, test bodies and advisers; commission bounded specialist work and organise review of content beyond your own competence.
• Guide customer pilots, document evidence gaps and shape a repeatable assurance service. Develop the regulatory team, review process and budget as demand grows.

Your first 90 days

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

Days 1–30: define one priority use case and market; deliver the applicability map, evidence-gap register and specialist review needs.

Days 31–60: produce a reviewed evidence framework, sample assessment workflow and acceptance criteria for the first NOMOS pilot.

Days 61–90: run a pilot evidence review with available partners, document limitations and corrective actions, and deliver a controlled method and roadmap for the next use case.

Essential experience

• Practical responsibility for robotics, machinery or closely related industrial product compliance, conformity assessment or safety assurance, with examples of evidence used in a real assessment or deployment decision.
• Ability to interpret relevant UK and/or EU product requirements and translate them into engineering and documentation tasks. You identify jurisdiction and application limits rather than assume one route fits every system.
• Experience building or reviewing technical evidence, risk assessments, safety arguments or technical documentation with engineering teams.
• A disciplined approach to requirement traceability, version control, review quality and defensible claims. You can distinguish a documented assertion from verified evidence.
• Ability to explain complex requirements plainly and to work hands-on in an early-stage business, making practical decisions while escalating specialist questions appropriately.

Useful, but not required

Experience with AI-enabled machinery, functional safety, industrial cybersecurity, testing organisations or assurance software; relevant engineering, safety or regulatory qualifications. We do not expect one person to be the specialist in every legal, safety and security domain.

Scope and support

You own robotics regulatory and assurance methodology. Financial-services permissions and insurance operating controls sit with the insurance lead and qualified advisers. You will work with appropriate specialists for legal interpretations and specialist safety assessments. Optimising Technologies’s software must not present an evidence report as regulatory approval or certification.

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 a robotics or machinery assessment you personally led or materially delivered. What evidence did you own and what decision did it support?
• Give an example of turning a requirement into a practical engineering or evidence workflow. What was difficult?
• How would you establish the boundaries of an automated regulatory evidence product, and when would you require specialist or independent review?