{"@context":"https://schema.org","@type":"JobPosting","title":"Clinical Safety & AI Assurance Lead","description":"

UK | Initial part-time / fractional | £50,000–£60,000 FTE equivalent (£450–£600/day depending on experience)

Start: Upon acquisition of our first healthcare client

RiskLine is building an AI assurance platform for healthcare.

Our focus is simple:

Help healthcare organisations and AI/health-tech vendors continuously understand, evidence and manage the clinical, regulatory and AI-governance risks of AI-enabled systems across UK and EU regulatory environments.

We are looking for an experienced Clinical Safety & AI Assurance Lead to work with us as we move from MVP into our first healthcare deployments.

Clinical Safety & AI Assurance Lead

to work with us as we move from MVP into our first healthcare deployments.

This is not a traditional compliance or documentation role.

You will help us turn real clinical-safety expertise into a product that can continuously identify, test, evidence and monitor risks across the lifecycle of healthcare AI.

What you will do

• Define and validate RiskLine's clinical-risk assessment and assurance model.

• Help translate clinical safety practice into structured, testable controls that can be represented within software.

• Review and challenge our approach to DCB0129/DCB0160, clinical-risk management, hazard identification, mitigations and evidence.

• Design realistic clinical-risk scenarios and test cases for AI-enabled healthcare systems.

• Test RiskLine against real-world AI use cases including clinical decision support, diagnostics, summarisation, documentation, patient-facing AI and other digital-health applications.

• Help us distinguish genuine clinical risk from low-value administrative/compliance activity.

• Work with AI vendors to understand the risks of their products before and after deployment.

• Work with healthcare organisations to understand the risks introduced when AI systems are deployed into real clinical workflows.

• Help define what should be monitored continuously rather than assessed only once.

• Review RiskLine outputs for clinical relevance, accuracy, proportionality and usability.

• Help develop evidence and reporting that a Clinical Safety Officer, healthcare organisation, AI vendor or auditor could actually use.

• Work closely with our engineering team to convert clinical requirements into product features and automated assurance tests.

• Participate in client discovery, product demonstrations and early customer implementations.

What we are looking for

You should ideally be a UK-registered healthcare professional with substantial experience in clinical safety, digital health, health technology or patient-safety governance.

Particularly valuable experience includes:

DCB0129 / DCB0160

Clinical Risk Management

Clinical Safety Officer experience

NHS digital technology

Digital health / HealthTech

AI-enabled healthcare

Medical devices / SaMD

ISO 14971

ISO 13485

DTAC

Clinical risk assessment and hazard management

Experience working on both the technology supplier/manufacturer and healthcare-provider/deployer sides would be particularly valuable.

technology supplier/manufacturer

and

healthcare-provider/deployer

sides would be particularly valuable.

You do not need to be a software engineer.

However, you must be comfortable working closely with engineers and challenging how software represents clinical risk.

What success looks like

Within the first 90 days, you should help us:

Validate RiskLine's clinical-risk model against real healthcare use cases.Establish a practical clinical-risk taxonomy suitable for software implementation.Create a library of representative healthcare AI risk scenarios and test cases.Validate our approach to DCB0129/DCB0160 and related clinical-safety evidence.Test the product with at least one AI/HealthTech vendor and/or healthcare organisation.Identify gaps between conventional clinical-safety assurance and continuous AI assurance.Help turn those gaps into concrete RiskLine product capabilities.Establish a repeatable clinical-assurance methodology that can scale beyond a single customer.

Validate RiskLine's clinical-risk model against real healthcare use cases.

Establish a practical clinical-risk taxonomy suitable for software implementation.

Create a library of representative healthcare AI risk scenarios and test cases.

Validate our approach to DCB0129/DCB0160 and related clinical-safety evidence.

Test the product with at least one AI/HealthTech vendor and/or healthcare organisation.

Identify gaps between conventional clinical-safety assurance and continuous AI assurance.

Help turn those gaps into concrete RiskLine product capabilities.

Establish a repeatable clinical-assurance methodology that can scale beyond a single customer.

The person we're looking for

You are probably someone who has thought:

\"Healthcare technology assurance needs to become more practical, continuous and risk-proportionate.\"

You enjoy working between clinical practice, regulation and technology.

You are comfortable saying:

\"This looks compliant, but I'm not convinced it is actually safe.\"

And equally comfortable saying:

\"This requirement adds little safety value in this particular context.\"

You can explain complex clinical-risk concepts to engineers.

You can challenge engineers without needing to become one.

And you want to help shape a new product rather than simply operate an existing process.

Engagement

We expect the initial engagement to be part-time/fractional, approximately 2 days per week, increasing as our healthcare customer base grows.

part-time/fractional

, approximately

2 days per week

, increasing as our healthcare customer base grows.

Initial compensation:

£55,000–£70,000 FTE equivalent / approximately £500–£650 per day

with the possibility of moving to a full-time position as RiskLine acquires additional healthcare customers.

Selection process

Candidates will be assessed on:

• Clinical safety expertise

• DCB0129/DCB0160 knowledge

• Practical clinical-risk judgement

• Healthcare AI/HealthTech understanding

• Ability to translate clinical risk into structured controls

• Ability to work with engineers

• Product-thinking and commercial pragmatism

• Understanding of supplier vs deploying-organisation responsibilities

• Ability to work in an early-stage startup environment

Qualifying questions

Please answer these briefly when applying with a cover letter and your resume, please email it to us at northstar.coah@icloud.com

1. What is your experience with DCB0129 and/or DCB0160?

What is your experience with DCB0129 and/or DCB0160?

2. Give one example where you identified a clinically significant risk in a digital-health or technology-enabled workflow that might otherwise have been missed.

Give one example where you identified a clinically significant risk in a digital-health or technology-enabled workflow that might otherwise have been missed.

3. How would you assess the clinical risk of an AI system that summarises clinical notes?

How would you assess the clinical risk of an AI system that summarises clinical notes?

4. What would you continuously monitor after an AI healthcare product has passed its initial clinical-safety assessment?

What would you continuously monitor after an AI healthcare product has passed its initial clinical-safety assessment?

5. How would your approach differ between an AI vendor developing a product and an NHS organisation deploying that product?

How would your approach differ between an AI vendor developing a product and an NHS organisation deploying that product?

6. Describe a situation where you disagreed with a compliance or assurance requirement because it was disproportionate to the actual clinical risk.

Describe a situation where you disagreed with a compliance or assurance requirement because it was disproportionate to the actual clinical risk.

7. How comfortable are you working directly with software engineers to define product requirements and test cases?

How comfortable are you working directly with software engineers to define product requirements and test cases?

8. If RiskLine showed a customer that an AI system's risk controls had degraded after deployment, what evidence would you expect to see before recommending action?

If RiskLine showed a customer that an AI system's risk controls had degraded after deployment, what evidence would you expect to see before recommending action?

9. What do you believe is currently missing from the way healthcare organisations assure AI systems?

What do you believe is currently missing from the way healthcare organisations assure AI systems?

10. Please provide an example of a clinical-risk assessment, hazard analysis, safety case or equivalent work you have personally contributed to. Confidential information can be anonymised.

10.

Please provide an example of a clinical-risk assessment, hazard analysis, safety case or equivalent work you have personally contributed to. Confidential information can be anonymised.

RiskLine

AI assurance for healthcare — continuously evidenced, clinically grounded.

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