Senior Applied AI Engineer

• Proven track record delivering AI models, systems and products to production in a consultancy or AI-driven product organisation.
• Strong programming (Python and the wider tech stack), system design and testing methodologies.
• Experience integrating models / LLMs and deploying on cloud platforms (AWS and/or Databricks), with solid CI/CD practice.
• Able to own delivery, manage stakeholders, and guide other engineers with confidence.
• Depth in a speciality: GenAI/ML (RAG, agentic workflows), Data Science, Data Engineering, Product/Full-Stack, or Platform/MLOps.
• AWS and/or Databricks certifications; experience of responsible-AI and production monitoring.

• Remote-first working with flexibility around client needs.
• Private Medical Insurance. 
• Opportunity to work on meaningful AI projects across multiple industries.
• A collaborative culture focused on learning, excellence and continuous improvement.
• Competitive salary with clear progression pathways.

As trusted partners of AWS and Databricks, we help organisations design, build and scale intelligent systems that deliver measurable business outcomes. We lead from the front in Generative and Applied AI adoption - guiding clients from uncertainty to confident, production-grade delivery.

We are looking for a talented Senior Applied AI Engineer where you will own the outcomes of an engagement or workstream: defining success, measuring business impact, and managing delivery and technical risk.

You will design AI and GenAI systems end-to-end, guide other engineers, and act as a trusted technical contact for clients.

The role is remote based in UK with the occasional travel to company events.

• Delivery & impact: Own workstream and engagement outcomes; define success, measure business impact, and balance technical debt, speed and scalability.
• AI & engineering craft: Design AI systems end-to-end across the lifecycle; make and justify key trade-offs; evaluate model performance beyond simple accuracy.
• Collaboration: Explain AI concepts, trade-offs and limitations to technical and non-technical clients; lead code reviews; resolve technical disagreements constructively.
• Growth & capability: Mentor engineers; contribute reusable components, accelerators and best practice; continuously improve how the team delivers.

Desirable