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- Tasks: Lead the design and delivery of cutting-edge AI solutions for diverse clients.
- Company: Global consulting business with a focus on innovation and collaboration.
- Benefits: Competitive salary, bonus potential, hybrid work model, and flexible start date.
- Other info: Opportunity to work with emerging technologies and enjoy excellent career growth.
- Why this job: Shape the future of AI while mentoring a talented team and solving real-world challenges.
- Qualifications: Strong software engineering skills, experience in AI/ML systems, and client-facing abilities.
The predicted salary is between 90000 - 120000 ÂŁ per year.
Work model: hybrid – 2-3 days per week onsite
Salary: ÂŁ90,000 - ÂŁ120,000 + 10-15% bonus
Start date: ASAP but can be flexible depending on individual notice period
One of our partners, a global consulting business is seeking a Senior Principal AI Engineer to lead the design and delivery of cutting‑edge, production‑grade AI solutions across complex client environments. This is an exciting opportunity to build a capable team from the ground up and also remain hands‑on turning real business challenges into scalable, secure, and responsible AI systems. Consultancy industry experience is not a must but the type of profile that would excel in this role is someone who is comfortable in a client facing role and can provide advice through the discovery phase, do demos and work with clients through their capabilities.
What You’ll Do
- Design, develop, and deploy end‑to‑end AI/ML systems—from ML to generative AI
- Create robust, production‑ready pipelines (data ingestion, modelling, deployment, monitoring)
- Implement MLOps best practices including CI/CD, versioning, automated re‑training, and rollback
- Ensure solutions are scalable, secure, and high‑performing in real‑world environments
- Define AI architectures aligned to client needs and long‑term sustainability
- Evaluate and introduce emerging technologies (LLMs, GenAI, vector databases) where they add real value
- Act as a trusted advisor, guiding trade‑offs and implementation strategies
- Mentor engineers and data scientists through hands‑on guidance and reviews
What You Bring
- Strong software engineering foundation (Python essential)
- Proven track record delivering production AI/ML systems
- Hands‑on experience with frameworks like PyTorch, TensorFlow, or scikit‑learn
- Solid understanding of MLOps and model deployment
- Experience working with cloud platforms (Azure, AWS or GCP)
If this fits your experience and skill set, please apply for immediate consideration.
Senior Principal AI Engineer employer: Synapri
Contact Detail:
Synapri Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Principal AI Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and tech space. Attend meetups, webinars, or industry events where you can chat with potential employers or colleagues. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that highlight your experience with frameworks like PyTorch or TensorFlow. This will give you an edge during interviews and demonstrate your hands-on expertise.
✨Tip Number 3
Prepare for client-facing scenarios! Since this role involves working closely with clients, practice explaining complex AI concepts in simple terms. Role-play with a friend or mentor to build your confidence in these discussions.
✨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. So, get your application in and let’s make it happen!
We think you need these skills to ace Senior Principal AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Principal AI Engineer role. Highlight your hands-on experience with AI/ML systems and any client-facing roles you've had. 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 excited about this role and how your background aligns with our needs. Don’t forget to mention your experience with MLOps and cloud platforms, as these are key for us.
Showcase Your Projects: If you've worked on any relevant projects, make sure to include them in your application. Whether it's a personal project or something from your previous job, we love seeing real-world applications of your skills, especially in AI/ML.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at Synapri
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and ML systems. Be ready to discuss your experience with frameworks like PyTorch and TensorFlow, and have examples of production-grade solutions you've delivered. This will show that you're not just familiar with the theory but can also apply it in real-world scenarios.
✨Showcase Your Client-Facing Skills
Since this role involves client interaction, prepare to demonstrate your ability to communicate complex ideas clearly. Think of past experiences where you've successfully advised clients or led discussions. Practising how you present technical concepts in a digestible way can really set you apart.
✨Highlight Your MLOps Knowledge
Be ready to talk about MLOps best practices, especially around CI/CD and automated re-training. Prepare specific examples of how you've implemented these practices in previous roles. This will show that you understand the importance of maintaining high-performance AI systems in production.
✨Prepare for Technical Challenges
Expect some technical questions or challenges during the interview. Brush up on your coding skills, particularly in Python, and be prepared to solve problems on the spot. Practising common algorithms or system design questions can help you feel more confident when tackling these challenges.