Data and AI - AI Engineer

Data and AI - AI Engineer

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
Wavestone

At a Glance

  • Tasks: Join a dynamic team to shape AI solutions for top-tier clients.
  • Company: Wavestone, a leader in Data & AI transformations.
  • Benefits: Competitive salary, flexible work options, and tailored training.
  • Other info: Embrace a vibrant culture with opportunities for mentorship and personal growth.
  • Why this job: Make a real impact in the evolving AI landscape while growing your career.
  • Qualifications: Experience in AI engineering and strong communication skills required.

The predicted salary is between 60000 - 80000 £ per year.

Joining Wavestone's UK Data & AI Service Line offers the opportunity to help shape large‑scale AI and data transformations for FTSE100 organisations and enterprise clients. Our team is rapidly growing as clients increasingly rely on us to design, build, and scale modern AI solutions across their organisations. You will be part of a high‑performing consulting and engineering team delivering both advisory and hands‑on implementation across AI strategy, AI engineering, GenAI solutions, and modern AI architecture patterns. This role is intentionally platform‑agnostic. While experience with tools such as Anthropic Claude, OpenAI models (e.g. Codex / GPT), and other frontier or open‑source LLMs is valuable, we are primarily looking for individuals who understand core AI engineering principles and can apply them across ecosystems.

This is an ideal role for someone who combines:

  • Deep technical and coding capability, with the ability to communicate complex concepts clearly to non‑technical audiences
  • Strong understanding of AI/GenAI systems and architecture
  • Experience building agentic, production‑grade AI solutions
  • The ability to operate across the full lifecycle: from strategy to design to build to deploy and scale

As a senior member of the Data & AI practice, your key responsibilities will cover client delivery, business development, people development, and key contribution to our thought leadership. Depending on your level of experience you will be expected to:

  • Business Development: Act as a trusted subject‑matter expert in AI engineering and GenAI during pre‑sales and sales activity. You will help identify opportunities, shape solution approaches, and contribute to proposals, RFP responses, and go‑to‑market initiatives. You will also develop compelling demos, prototypes, and technical narratives that demonstrate the value and feasibility of modern AI solutions, supporting the growth of Wavestone’s Data & AI footprint across key accounts.
  • Thought Leadership & Proposition Ownership: Play a key role in shaping Wavestone’s AI and GenAI propositions, bringing forward innovative approaches to agentic systems, retrieval architectures, evaluation frameworks, and enterprise AI engineering. You will contribute to thought leadership through articles, insights, and event participation, and help develop reusable accelerators, toolkits, and playbooks that address common client challenges. Your work will strengthen our market presence and help position Wavestone as a leader in practical, scalable AI delivery.
  • People Development: Support the growth of our Data & AI community by mentoring consultants and engineers, sharing best practice, and providing technical guidance across architecture, engineering, and delivery. You will help build internal capability through knowledge‑sharing, training, and the development of reusable methodologies and frameworks. Where appropriate, you may also contribute to line management and career development within the practice.
  • Maintain Expertise: Stay at the forefront of the rapidly evolving AI/GenAI landscape, maintaining deep expertise in LLMs, agentic systems, RAG patterns, evaluation techniques, and cloud‑native AI tooling. You will continuously explore emerging technologies and engineering patterns, bringing forward new ideas that enhance client delivery and strengthen Wavestone’s internal capability.

Qualifications Core Skills & Experience

  • Proven experience building AI/LLM‑powered applications in production
  • Deep understanding of AI/GenAI fundamentals, including model behaviour, limitations, and evaluation
  • Experience designing and implementing RAG systems
  • Experience designing and implementing agentic workflows / multi‑step reasoning systems
  • Experience designing and implementing tool‑using AI applications
  • Strong system‑design and architecture skills (APIs, data pipelines, distributed systems)
  • Experience with cloud platforms (AWS, Azure, GCP)
  • Ability to make technical trade‑offs (cost, latency, accuracy, scalability)
  • Experience working in client‑facing or consulting environments, as well as leading teams and projects
  • Strong communication and stakeholder management skills
  • Experience across multiple AI platforms (e.g., Claude, GPT, open‑source models)
  • Familiarity with orchestration frameworks (LangChain, LlamaIndex, etc.)
  • Experience optimising AI systems for performance, cost, and reliability
  • Knowledge of enterprise architecture and regulated environments
  • Experience with AI agents, copilots, or automation systems
  • Exposure to AI governance, safety, and responsible AI practices
  • Contributions to thought leadership, open‑source, or internal capability building

Additional Information

Wavestone values and positive way. Elevate client satisfaction by impacting high‑growth business across US, UK, and Europe. Shape culture, enhance value propositions, and foster business development. Nurture employee growth with Wavestone horizon career path, competitive compensation, transparent salary policy, tailored training, and internal mobility. Embrace a collective mindset within a barrier‑free, collaborative team. Engage in vibrant people culture through regular events, meetings, and committees. Experience ethical responsibility with flexible work options, strong CSR commitment, and a culture promoting work‑life balance and time‑off. Competitive salary and bonus scheme. Income protection insurance, 5% company pension, private health and dental cover, life insurance, company share scheme. Additional flexible benefits you can select from such as additional holidays, additional pension contributions, subsidized gym, subscriptions to wellbeing apps, Netflix, retail vouchers. 25 days annual leave.

Travel and Location

Employees are not required to work in a Wavestone office on a full‑time basis but are required to commute to the office /client site, whenever necessary. Wavestone UK office is in the heart of the city of London. Note: Mandatory 2-3 days per week in Wavestone office / client site during probation.

Diversity and Inclusion

At Wavestone, we celebrate diversity and inclusion. We have a strong global CSR agenda and an active Diversity & Inclusion committee with Gender Equality, LGBTQ+, Disability Inclusion, Social Mobility and Anti‑Racism networks. If you need flexibility, assistance, or an adjustment to our recruitment process due to a disability or impairment, please reach out to us to discuss this.

Data and AI - AI Engineer employer: Wavestone

Wavestone is an exceptional employer that fosters a vibrant and inclusive work culture, offering employees the chance to engage in meaningful AI and data transformations for leading organisations. With a strong commitment to employee growth through tailored training, competitive compensation, and a transparent salary policy, Wavestone encourages collaboration and innovation within its diverse teams. Located in the heart of London, the company provides flexible work options and a comprehensive benefits package, ensuring a healthy work-life balance while empowering staff to thrive in their careers.

Wavestone

Contact Details:

Wavestone Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data and AI - AI Engineer

Tip Number 1

Network like a pro! Get out there and connect with folks in the AI and data space. Attend meetups, webinars, or industry events. You never know who might be looking for someone just like you!

Tip Number 2

Show off your skills! Create a portfolio showcasing your AI projects, demos, or prototypes. This is your chance to shine and demonstrate your technical prowess to potential employers.

Tip Number 3

Prepare for interviews by brushing up on your communication skills. Practice explaining complex AI concepts in simple terms. Remember, you’ll need to impress both technical and non-technical audiences!

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 Data and AI - AI Engineer

AI Engineering
GenAI Solutions
AI Architecture
Deep Technical and Coding Capability
Communication of Complex Concepts
Production-Grade AI Solutions
Full Lifecycle Management

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the AI Engineer role. Highlight your experience with AI/GenAI systems and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!

Showcase Your Technical Skills:Don’t hold back on your technical prowess! Include specific examples of AI solutions you've built or contributed to, especially those that demonstrate your understanding of core AI engineering principles. This is your chance to shine!

Communicate Clearly:Remember, we value clear communication! When describing your experiences, aim to explain complex concepts in a way that’s easy to understand. This will show us you can bridge the gap between technical and non-technical audiences.

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 gives you a chance to explore more about our culture and values!

How to prepare for a job interview at Wavestone

Know Your AI Fundamentals

Make sure you brush up on your understanding of AI and GenAI principles. Be ready to discuss model behaviour, limitations, and evaluation techniques. This will show that you have a solid foundation and can apply these concepts across different ecosystems.

Showcase Your Technical Skills

Prepare to demonstrate your coding capabilities and system design skills. Bring examples of AI/LLM-powered applications you've built in production. Highlight your experience with cloud platforms and orchestration frameworks, as this will be crucial for the role.

Communicate Clearly

Since you'll need to explain complex concepts to non-technical audiences, practice simplifying your explanations. Use relatable analogies or examples to make your points clear. This will help you stand out as someone who can bridge the gap between technical and non-technical stakeholders.

Engage in Thought Leadership

Be prepared to discuss your contributions to thought leadership in AI. Whether it's articles, insights, or participation in events, showcasing your proactive approach to sharing knowledge will demonstrate your commitment to the field and your potential value to the team.