At a Glance
- Tasks: Lead AI/ML projects, mentor teams, and ensure high-quality delivery.
- Company: Dynamic tech firm with a focus on innovation and collaboration.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Flexible working arrangements with potential for significant career advancement.
- Why this job: Shape the future of AI while leading talented teams and making an impact.
- Qualifications: Proven technical delivery experience and strong leadership skills.
The predicted salary is between 115000 - 125000 £ per year.
We are seeking an AI Engineering Lead to sit at the top of our client’s delivery structure. This role bridges strategic leadership and hands‑on delivery, providing day‑to‑day technical direction to a team of consultants and ensuring high‑quality outcomes across multiple client environments. You will remain deeply involved in solution design and build, while also shaping ways of working, mentoring engineers and consultants, and supporting pre‑sales activity to secure and expand engagements.
Location: Hybrid, United Kingdom (UK‑wide flexibility; occasional London presence a few days per month when required)
Salary: £115,000 - £125,000 per year (DOE)
Notice periods: Longer notice periods (including up to 6 months) can be considered for the right candidate
Key Responsibilities:
- Lead end-to-end delivery of AI/ML and GenAI programmes: discovery, architecture, build, deployment and operationalisation.
- Act as the senior technical authority for clients, translating complex concepts into clear defined strategies for senior non‑technical stakeholders.
- Own solution quality: engineering standards, code reviews, model governance, security, and delivery assurance.
- Provide technical leadership and coaching; build progression frameworks and mentoring for consultants.
- Drive pre‑sales: shape propositions, run technical workshops, produce SOW inputs, estimates.
- Partner with stakeholders across Data Services to deliver integrated outcomes (e.g., BI and analytics alongside AI solutions).
Technical Scope:
- Platform‑agnostic engineering mindset; able to work across varied client stacks.
- Experience with cloud AI services and MLOps/LLMOps (e.g., Azure AI Foundry, AWS SageMaker and/or Bedrock).
- Strong software engineering practices: Python, APIs, containerisation, CI/CD, IaC, testing, observability and production support.
- Modern ML/GenAI approaches: feature engineering, model training, evaluation, RAG, prompt engineering, guardrails, and responsible AI.
- Data engineering fundamentals: pipelines, data quality, governance, and working with structured/unstructured data.
Requirements:
- Demonstrable hands‑on technical delivery at senior level (not purely advisory).
- Strong senior stakeholder management; able to adjust communication style for technical and non‑technical audiences.
- Proven experience leading multi‑disciplinary teams and mentoring others.
- Pre‑sales experience with measurable impact (pipeline contribution, proposals, or deal support).
- Right to work in the United Kingdom.
AI Engineering Lead employer: Gravitas Group
As an AI Engineering Lead at our company, you will thrive in a dynamic and innovative environment that champions collaboration and professional growth. With a strong focus on mentorship and technical leadership, we offer a unique opportunity to shape the future of AI solutions while enjoying the flexibility of a hybrid work model across the UK. Our commitment to high-quality outcomes and employee development makes us an exceptional employer for those seeking meaningful and rewarding careers in technology.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineering Lead
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and tech space. Attend meetups, webinars, or even local events. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI/ML. This is your chance to demonstrate your hands-on experience and technical delivery. Make sure it’s easy to access and share!
✨Tip Number 3
Prepare for interviews by brushing up on your communication skills. Practice explaining complex AI concepts in simple terms. Remember, you’ll be talking to both technical and non-technical stakeholders, so adaptability is key!
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals like you. Plus, it gives you a better chance to showcase your fit for the role right from the start.
We think you need these skills to ace AI Engineering Lead
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the AI Engineering Lead role. Highlight your hands-on technical delivery and leadership experience, as well as any relevant pre-sales activities you've been involved in.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of how you've led teams, mentored others, and delivered successful AI/ML projects. Keep it engaging and personal!
Showcase Your Technical Skills:In your application, don't shy away from detailing your technical expertise. Mention your experience with cloud AI services, software engineering practices, and modern ML approaches. We want to see how you can bring value to our team!
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 makes the process smoother for everyone involved!
How to prepare for a job interview at Gravitas Group
✨Know Your Tech Inside Out
As an AI Engineering Lead, you’ll need to demonstrate your technical prowess. Brush up on the latest AI/ML technologies and be ready to discuss your hands-on experience with cloud services like Azure AI Foundry or AWS SageMaker. Prepare to explain complex concepts in simple terms, as you'll be translating these for non-technical stakeholders.
✨Showcase Your Leadership Skills
This role requires strong leadership and mentoring abilities. Be prepared to share examples of how you've led multi-disciplinary teams and coached engineers. Highlight specific instances where your guidance has led to successful project outcomes or improved team performance.
✨Prepare for Pre-Sales Scenarios
Since pre-sales activity is a key part of this role, think about your past experiences in shaping propositions and running technical workshops. Have a few success stories ready that showcase your impact on pipeline contributions or proposals, as this will demonstrate your ability to drive business growth.
✨Understand the Client's Needs
Research the company and its clients thoroughly. Understand their challenges and how your expertise can provide solutions. During the interview, ask insightful questions that show you’re not just interested in the role, but also in how you can contribute to their success and deliver integrated outcomes across various services.
