At a Glance
- Tasks: Lead the design and deployment of cutting-edge AI systems for top financial institutions.
- Company: Join a leading global consultancy known for its entrepreneurial culture.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace encouraging underrepresented talent.
- Why this job: Shape the future of AI in finance and make a real impact.
- Qualifications: Experience with LLMs, Python, and MLOps; strong leadership skills.
The predicted salary is between 80000 - 100000 € per year.
We're partnered with a leading global management and technology consultancy seeking a talented Lead AI Engineer to join their Technology Delivery team in London. Known for their entrepreneurial culture and deep expertise across financial services, this is an exceptional opportunity to architect and deliver next-generation AI systems at the heart of some of the world's most complex financial institutions.
You'll take a hands-on leadership role designing and deploying generative AI and agentic systems end-to-end - from early architecture through to production - working across multidisciplinary teams and directly shaping how leading financial institutions adopt AI at scale.
What you'll be doing:
- Designing and delivering autonomous AI systems that bring together multi-modal LLMs.
- Building agentic workflows that connect AI agents to live data sources and APIs, drawing on prompt engineering and RAG to drive accuracy and relevance.
- Optimising and shipping large language and multi-modal models into production, balancing performance, latency, and reliability at enterprise scale.
- Developing robust MLOps pipelines and full-stack applications that underpin scalable, production-ready AI deployments.
- Acting as a trusted advisor to clients and internal teams on GenAI strategy, making complex AI concepts accessible and actionable for business stakeholders.
What we're looking for:
- A strong record of taking LLMs and multi-modal models from development through to production, with real experience of operating at scale.
- Solid Python engineering skills, with a proven ability to build and ship backend systems and APIs.
- Hands-on knowledge of MLOps, cloud-native infrastructure, and the observability practices that keep AI systems performing in the real world.
- Comfortable leading technical teams and bridging the gap between engineering and business - able to bring stakeholders along on complex decisions in fast-moving agile environments.
- Practical experience with agentic frameworks such as LangChain or LlamaIndex.
We encourage underrepresented talent to apply to all our roles & support accessibility needs.
Lead AI Engineer employer: Primis
Join a leading global management and technology consultancy in London, where innovation meets an entrepreneurial spirit. As a Lead AI Engineer, you'll thrive in a collaborative work culture that prioritises employee growth and development, offering unique opportunities to shape the future of AI in financial services. With a commitment to diversity and inclusion, this company not only values your expertise but also supports your career journey in a dynamic and rewarding environment.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Engineer
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving LLMs and AI systems. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to AI engineering. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to join our team.
We think you need these skills to ace Lead AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Lead AI Engineer role. Highlight your experience with LLMs, MLOps, and any relevant projects you've worked on. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for this position. Don’t forget to mention your hands-on leadership experience and ability to bridge technical and business gaps.
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them in your application. Whether it's deploying AI systems or building APIs, we love seeing real-world examples of your work. It helps us understand your practical experience better!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our awesome team at StudySmarter!
How to prepare for a job interview at Primis
✨Know Your AI Stuff
Make sure you brush up on the latest trends in AI, especially around LLMs and multi-modal models. Be ready to discuss your hands-on experience with these technologies and how you've successfully deployed them in production.
✨Showcase Your Leadership Skills
Since this role involves leading technical teams, prepare examples of how you've bridged the gap between engineering and business. Think about times when you made complex AI concepts accessible to stakeholders and how you navigated fast-moving environments.
✨Get Familiar with MLOps
Understand the ins and outs of MLOps pipelines and cloud-native infrastructure. Be prepared to talk about your experience in optimising AI systems for performance and reliability, as well as any observability practices you've implemented.
✨Prepare for Technical Questions
Expect some deep dives into your technical skills, particularly in Python and backend systems. Brush up on your knowledge of agentic frameworks like LangChain or LlamaIndex, and be ready to discuss how you've used them in your projects.
