- Company Name
- Humand Talent
- Job Title
- AI Engineer - 70% IC, 30% Leadership - £90-110k flexible - (ID45598)
- Job Description
-
**Job Title**
AI Engineer – Generative AI (70% Individual Contributor, 30% Leadership)
**Role Summary**
Lead end‑to‑end design, implementation and deployment of generative AI applications. Balance hands‑on engineering with mentoring, owning cloud infrastructure, data pipelines, and production optimisation. Work cross‑functionally with data scientists, product managers and other engineers to deliver scalable, reliable AI systems that provide real‑world value.
**Expectations**
- Deliver production‑ready generative AI solutions and drive technical direction.
- Mentor junior engineers and shape team practices.
- Own end‑to‑end lifecycle: prototyping, fine‑tuning, integration, testing and deployment.
- Collaborate with product, UX and ops teams to ensure solutions meet user needs and business goals.
- Continuously improve infrastructure, workflows and safety of AI services.
**Key Responsibilities**
1. Architect and build generative AI systems using OpenAI APIs, LLM agents, and prompt‑engineering frameworks.
2. Fine‑tune, customise and evaluate large language models for specific application needs.
3. Develop backend services (Python) and AI pipelines, ensuring scalability and maintainability.
4. Design and maintain cloud‑based deployments on AWS, GCP or Azure; manage IAM, networking, monitoring and cost optimisation.
5. Implement CI/CD pipelines, containerisation (Docker, Kubernetes) and real‑time API endpoints.
6. Integrate retrieval‑augmented generation (RAG) and function‑calling architectures.
7. Provide technical guidance, code reviews and knowledge transfer to peers and junior staff.
8. Participate in cross‑disciplinary design reviews and sprint planning.
**Required Skills**
- Strong programming in Python; experience building backend services and data pipelines.
- Hands‑on experience with generative AI tools: OpenAI APIs, LLM fine‑tuning, prompt engineering, RAG, function‑calling.
- Proficiency with at least one major cloud platform (AWS, GCP, Azure).
- Familiarity with CI/CD, containerisation (Docker, Kubernetes), and real‑time API development (REST/GraphQL).
- Solid understanding of ML/AI best practices: data governance, model monitoring, and safety.
- Excellent communication and teamwork; demonstrated ability to mentor and influence technical direction.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Data Science or a related technical field.
- Relevant AI or cloud certifications (e.g., AWS Certified Machine Learning, GCP Professional Data Engineer, Azure ML Engineer) are a plus.
Oxfordshire, United kingdom
Hybrid
17-02-2026