Client‑Facing GenAI Engineer — Hybrid London

Client‑Facing GenAI Engineer — Hybrid London

Full-Time 80000 - 100000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Deliver innovative GenAI solutions and collaborate with clients to solve complex challenges.
  • Company: Keyrus UK, a leader in AI-driven solutions with a hybrid work culture.
  • Benefits: Flexible working arrangements, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic role with opportunities to shape the future of AI solutions.
  • Why this job: Join a forward-thinking team and make a real impact in the AI space.
  • Qualifications: Experience in AI engineering and strong communication skills.

The predicted salary is between 80000 - 100000 £ per year.

Keyrus UK is seeking a Forward Deployed AI Engineer to work hybrid in London, delivering cutting-edge Gen AI and AI-driven solutions for client engagements.

The role blends hands-on engineering with architectural judgment and business understanding, turning ambiguous challenges into measurable value.

You will co-create with stakeholders, secure data access, and deploy production-ready AI solutions while ensuring governance and transferable patterns for future engagements.

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Client‑Facing GenAI Engineer — Hybrid London employer: Keyrus Named Leader in Everest Group

At Keyrus UK, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our London office provides a hybrid working model, competitive benefits including private medical insurance, and a strong focus on career development through our Keyrus Learning Experience. Join us to tackle meaningful AI challenges while enjoying a supportive environment that values your growth and contributions.

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Contact Details:

Keyrus Named Leader in Everest Group Recruitment Team

We think you need these skills to ace Client‑Facing GenAI Engineer — Hybrid London

Python
Communication Skills
Problem-Solving Skills
SQL
Data Engineering
Attention to Detail
Data Pipeline Development