Generative AI Engineer
| Posting date: | 18 August 2025 |
|---|---|
| Salary: | £44,000 to £47,000 per year |
| Hours: | Full time |
| Closing date: | 17 September 2025 |
| Location: | Milton Keynes, Buckinghamshire |
| Remote working: | On-site only |
| Company: | GKV Enterprises ltd |
| Job type: | Permanent |
| Job reference: | GAIE_GAK_08_2025_06 |
Summary
We are looking for a highly skilled and passionate Generative AI Engineer to join our AI/ML team. In this role, you will design and build solutions using advanced generative AI models and deep learning techniques, collaborating with cross-functional teams to deliver impactful AI solutions that integrate seamlessly into business workflows.
Responsibilities
Collaborate with product, engineering, and research teams to integrate generative AI capabilities into applications and services.
Research, evaluate, and implement the latest advancements in generative AI and large language models (LLMs).
Develop, maintain, and iterate on prompt engineering strategies to optimize model outputs.
Apply advanced techniques including prompt tuning, RLHF, and benchmarking for performance and accuracy.
Work with vector databases (e.g., FAISS, PGVector, Pinecone) for RAG (retrieval-augmented generation) and semantic search use cases.
Design scalable, observable, and resilient AI pipelines for real-world applications.
Monitor and improve model performance, efficiency, and user experience on an ongoing basis.
Qualifications
- Strong experience in deep learning and NLP, particularly with LLMs and generative models.
- Proficiency in Python and ML libraries/frameworks (Hugging Face Transformers, LangChain, OpenAI APIs).
- Hands-on experience in prompt engineering, few-shot learning, and fine-tuning LLMs.
- Familiarity with ML Ops / LLMOps and distributed systems.
- Practical experience with vector databases and RAG pipelines.
- Solid understanding of system design, scalability, observability, and performance tuning.
- Strong analytical and problem-solving skills.
- Passion for exploring new AI/ML technologies and applying them to business problems.
Responsibilities
Collaborate with product, engineering, and research teams to integrate generative AI capabilities into applications and services.
Research, evaluate, and implement the latest advancements in generative AI and large language models (LLMs).
Develop, maintain, and iterate on prompt engineering strategies to optimize model outputs.
Apply advanced techniques including prompt tuning, RLHF, and benchmarking for performance and accuracy.
Work with vector databases (e.g., FAISS, PGVector, Pinecone) for RAG (retrieval-augmented generation) and semantic search use cases.
Design scalable, observable, and resilient AI pipelines for real-world applications.
Monitor and improve model performance, efficiency, and user experience on an ongoing basis.
Qualifications
- Strong experience in deep learning and NLP, particularly with LLMs and generative models.
- Proficiency in Python and ML libraries/frameworks (Hugging Face Transformers, LangChain, OpenAI APIs).
- Hands-on experience in prompt engineering, few-shot learning, and fine-tuning LLMs.
- Familiarity with ML Ops / LLMOps and distributed systems.
- Practical experience with vector databases and RAG pipelines.
- Solid understanding of system design, scalability, observability, and performance tuning.
- Strong analytical and problem-solving skills.
- Passion for exploring new AI/ML technologies and applying them to business problems.