AI Engineer
KBC Technologies UK LTD
Charing Cross, United Kingdom
4 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Charing Cross, United Kingdom
Tech stack
API
Artificial Intelligence
User Authentication
Azure
Databases
Information Retrieval
Message Broker
OAuth
Azure
JSON Web Token
Large Language Models
Kafka
Job description
We are seeking a highly skilled and experienced AI Engineer to join our team. The ideal candidate will bring deep expertise in building and deploying AI/ML solutions, particularly in areas like NLP, document understanding, and search/retrieval systems. You will work in a dynamic environment, collaborating across teams to design scalable AI-driven solutions and bring them into production., * Design, develop, and deploy AI/ML solutions with a focus on NLP, document understanding, and information retrieval.
- Integrate AI models into systems using APIs and message brokers such as REST and Kafka.
- Implement secure systems using modern authentication and authorization standards like OAuth2, JWT, and Azure AD.
- Apply best practices in AI model evaluation, tuning, and optimization.
- Work with LLM architectures and frameworks (OpenAI, Anthropic, LangChain, LlamaIndex) to build scalable and intelligent applications.
- Utilize vector databases (e.g., FAISS, Azure AI Search) and embedding models for semantic search and retrieval tasks.
- Execute and iterate on PoCs rapidly to evaluate feasibility and solution effectiveness.
- Collaborate with cross-functional teams and stakeholders to align AI solutions with business objectives.
Requirements
- 12+ years of total IT experience.
- Hands-on experience with production-grade AI/ML projects, including at least two successful deployments.
- Strong expertise in:
- API integration & inter-service communication (REST, Kafka)
- Authentication/Authorization (OAuth2, JWT, Azure AD)
- NLP techniques (NER, classification, chunking, summarization, QA)
- RAG architectures and working with LLMs (OpenAI, Anthropic, etc.)
- Vector databases (FAISS, Azure AI Search)