Senior AI Consultant

Omnis Partners
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist - AI Practice Team

Senior Data Scientist - AI Practice Team

Senior Consultant - Data Scientist

Senior Machine Learning Engineer

Data Engineering & Data Science Consultant

Data Engineering & Data Science Consultant

Technology Consultant – AI Specialist


Multiple Roles Available from Consultant ➡️VP ➡️Associate Director


Join a Global Leader in Management Consulting as they scale their UK AI Expert Team



£60k - £80k - £110k depending on level

Remote / Hybrid location in London



Are you a tech-savvy innovator passionate about harnessing the power of cutting-edge technology to transform businesses? Do you have deep expertise in developing LLMs and Generative AI solutions? If so, we want to hear from you!



We are currently partnered with a globally recognized management consulting firm at the forefront of technology solutions design to scale a team of 15 GenAI Consultants at varying levels.



They empower organizations with innovative solutions that drive growth, efficiency, and value. With a presence in over 50 countries, they collaborate with top-tier clients to solve their most pressing challenges.



The Role

As a Client-Facing Technology Consultant specializing in LLMs and Generative AI, you will:

  • Advise & Strategize: Partner with senior stakeholders to identify opportunities where LLMs and Generative AI can drive meaningful business outcomes.
  • Innovate & Build: Design, develop, and implement scalable AI solutions tailored to client needs, leveraging the latest advancements in natural language processing and generative AI.
  • Collaborate & Deliver: Work closely with multidisciplinary teams, including Data Scientists, Software Engineers, and Business Strategists, to deliver impactful AI solutions.
  • Educate & Inspire: Lead workshops and training sessions to demystify AI technologies and foster adoption among client teams.



What You Bring

  • Technical Expertise: Proven experience in developing and deploying LLMs (e.g., GPT, BERT) and Generative AI applications in a business or client facing setting.
  • Business Acumen: A strong ability to translate complex technical concepts into business value for non-technical audiences.
  • Client-Facing Skills: Exceptional communication and interpersonal skills, with a track record of building trusted relationships with clients.
  • Innovation Mindset: A passion for staying ahead of technology trends and driving creative, data-driven solutions.
  • Educational Background: A degree in Computer Science, AI, Engineering, or a related field. Advanced degrees are a plus.



Why This Opportunity?

  • Global Impact: Collaborate with industry-leading clients on transformative projects.
  • Career Growth: Accelerate your professional development with access to world-class training and mentorship.
  • Innovative Environment: Be part of a forward-thinking team that values curiosity, creativity, and innovation.
  • Inspiring Leadership:Work under the mentorship and guidance of a highly revered AI leader; Phd in AI, extensive experience in consulting and technology, passionate, energetic and highly engaging character

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.