At a Glance
- Tasks: Lead AI projects from concept to production in a dynamic cybersecurity environment.
- Company: Join a growing tech business at the forefront of AI innovation.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Other info: High ownership role with exciting R&D projects and career advancement potential.
- Why this job: Shape the future of AI in cybersecurity and make a real impact.
- Qualifications: Strong AI/ML engineering experience and Python development skills required.
The predicted salary is between 70000 - 90000 £ per year.
You will join a growing technology business at a pivotal stage in its AI journey. These are the first dedicated AI engineering hires in the team, so you will have the chance to shape how AI is designed, built, and deployed across a live cybersecurity product environment. Initially, your focus will sit within the cyber division, where you will work on AI-driven initiatives tied to vulnerability management, penetration testing workflows, remediation checking, intelligent reporting, and automation. Longer term, there is scope for the role to expand into wider product areas across the group.
This is a hands-on engineering role with real ownership. You will take AI projects from concept through to production, not just build prototypes and hand them over. You will be expected to design, develop, deploy, monitor, and maintain scalable AI services that integrate into existing platforms via APIs and microservices.
What They’re Looking For:
- The key requirement is strong, real-world AI engineering capability. They need someone who can build and deliver, not someone who has only experimented on the edges of AI.
- You will ideally bring:
- AI/ML engineering experience in production environments
- LLM development and orchestration experience
- Python development
- Cloud platform experience across AWS or Azure or GCP
- End-to-end delivery experience from idea and prototyping through to deployment and support
- Experience building scalable services and APIs
- Strong communication skills and the ability to work closely with developers and stakeholders
- A self-starting approach with the confidence to own your workload and move initiatives forward
- Cybersecurity knowledge is not essential. That can be taught. The non-negotiable is deep AI and machine learning expertise.
What You’ll Work With:
You will work across a modern AI and product environment, with plenty of room to influence standards and tooling as the function matures. Likely technologies and themes include:
- Python development
- OpenAI models
- Anthropic models
- AWS Bedrock
- LLM workflows
- Agentic AI systems
- Machine learning algorithms
- API-led microservices
- Cloud platforms
- Monitoring, management, and alerting
- Vulnerability management workflows
- AI-assisted report generation
- Security testing automation
The current product direction is centred on building AI capabilities as services outside the main platform, then integrating them back in via APIs. That means the work has a genuine R&D feel, but always with a clear path into production.
Nice to Haves:
- These are helpful, but not essential:
- Cybersecurity experience
- Penetration testing exposure
- Vulnerability management knowledge
- Agent-based system design
- Content analysis or anomaly detection experience
- MLOps understanding
- Enterprise environment experience
- Change control awareness
- KPI or ROI tracking experience
- Leadership or mentoring capability
- Product or solutions thinking
Why Join / Projects?
You will be joining very early in the AI build-out, which means high ownership, a broad remit, and the chance to make a visible impact. Early projects are expected to include:
- AI-powered remediation checking following penetration tests
- Worker or agent-style services that perform specific testing tasks and report findings back
- LLM-powered reporting and consultant support tools
- AI modules for external, web, cloud, and later internal testing use cases
- Statistical analysis and machine learning models for wider business applications over time
- Reusable AI services that can eventually support multiple products and business units
This role will suit someone who enjoys solving complex problems, working in ambiguity, and building things properly from the ground up. There is likely to be a blend of seniority across the hires, so candidates with leadership potential or experience guiding others will be particularly valuable. You will report initially into the cyber product and technology function, with close collaboration across product, architecture, engineering, and technical leadership.
Lead AI Engineer in Portsmouth employer: Prism Digital
Join a pioneering technology business at the forefront of AI innovation in cybersecurity, where you will have the unique opportunity to shape the future of AI engineering. With a strong emphasis on employee growth and a collaborative work culture, this role offers meaningful projects that allow for high ownership and the chance to make a significant impact. Enjoy the flexibility of remote work combined with occasional travel to vibrant locations like Leeds and Chester, fostering a dynamic environment for professional development and creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Engineer in Portsmouth
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. The more people you know, the better your chances of landing that Lead AI Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving LLMs and cloud platforms. This will give you an edge when discussing your hands-on experience during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and AI engineering knowledge. Practice coding challenges and be ready to discuss your end-to-end delivery experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Lead AI Engineer in Portsmouth
Some tips for your application 🫡
Show Your AI Skills:Make sure to highlight your real-world AI engineering experience in your application. We want to see how you've built and delivered AI solutions, not just dabbled in them. Use specific examples that showcase your expertise!
Tailor Your Application:Don’t just send a generic CV and cover letter. Tailor your application to reflect the key requirements mentioned in the job description. We love seeing candidates who take the time to connect their skills with what we’re looking for.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon and fluff. Make it easy for us to see why you’re the perfect fit for the Lead AI Engineer role!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Prism Digital
✨Know Your AI Inside Out
Make sure you brush up on your AI and machine learning knowledge. Be ready to discuss real-world applications, especially in production environments. They want someone who can build and deliver, so prepare examples of your past projects that showcase your hands-on experience.
✨Showcase Your Python Skills
Since Python development is key for this role, be prepared to talk about your coding experience. Bring along examples of code you've written or projects where you've used Python to solve complex problems. If you can, demonstrate your understanding of APIs and microservices as well.
✨Understand the Cybersecurity Landscape
While cybersecurity knowledge isn't essential, having a basic understanding will set you apart. Familiarise yourself with concepts like vulnerability management and penetration testing workflows. This will help you engage more effectively with the team and show your willingness to learn.
✨Be Ready to Discuss Ownership and Leadership
This role offers high ownership, so be prepared to share how you've taken initiative in previous roles. Talk about times when you've led projects or mentored others. Highlight your self-starting approach and how you can drive initiatives forward, even in ambiguous situations.
