About the role
AI Engineer
Enterprise Knowledge Base (EKB) Role Overview We are looking for an experienced
AI Engineer
to design, build, and deploy enterprise-grade AI solutions that enhance knowledge discovery, retrieval, and automation. The ideal candidate will have strong expertise in
Generative AI ,
Large Language Models (LLMs) ,
AI Agents , and modern AI application frameworks, with a passion for delivering scalable, production-ready solutions. Key Responsibilities
Design and develop AI-powered applications using
GenAI ,
LLMs ,
NLP , and
Agentic AI
technologies. Build intelligent
RAG (Retrieval-Augmented Generation)
solutions leveraging
Embeddings
and
Vector Databases . Develop and orchestrate
AI Agents
and
Multi-Agent Systems
to automate complex business workflows. Apply
Prompt Engineering
and
Context Engineering
techniques to optimise AI performance and accuracy. Implement AI solutions using frameworks such as
LangChain ,
LangGraph , and
MCP . Integrate AI services and enterprise platforms through
REST APIs
and cloud-native architectures. Deliver scalable, secure, and reliable solutions using
Python ,
SQL ,
Git , and
CI/CD
practices. Test, evaluate, and continuously improve
LLM
and
AI Agent
performance, reliability, and safety. Collaborate with business, data, and engineering teams to drive AI adoption and innovation. Required Skills
AI ,
Generative AI (GenAI) ,
Large Language Models (LLMs) ,
Natural Language Processing (NLP) Prompt Engineering ,
Context Engineering AI Agents ,
Agentic AI ,
Multi-Agent Systems LangChain ,
LangGraph ,
Model Context Protocol (MCP) RAG ,
Embeddings ,
Vector Databases Python ,
SQL ,
REST APIs Git ,
CI/CD Cloud Platforms (Azure, AWS, or GCP) LLM & AI Agent Testing and Evaluation Desirable Skills
Knowledge Graphs Semantic Search Responsible AI Token Optimisation & Cost Management AI Evaluations (Evals) Re-ranking Techniques Caching Strategies Preferred Experience
Experience designing and implementing
Enterprise Knowledge Bases (EKBs) , AI-powered enterprise search, knowledge management, or intelligent retrieval platforms. Experience delivering AI solutions from prototyping through to production deployment in enterprise environments.
TPBN1_UKTJ
Enterprise Knowledge Base (EKB) Role Overview We are looking for an experienced
AI Engineer
to design, build, and deploy enterprise-grade AI solutions that enhance knowledge discovery, retrieval, and automation. The ideal candidate will have strong expertise in
Generative AI ,
Large Language Models (LLMs) ,
AI Agents , and modern AI application frameworks, with a passion for delivering scalable, production-ready solutions. Key Responsibilities
Design and develop AI-powered applications using
GenAI ,
LLMs ,
NLP , and
Agentic AI
technologies. Build intelligent
RAG (Retrieval-Augmented Generation)
solutions leveraging
Embeddings
and
Vector Databases . Develop and orchestrate
AI Agents
and
Multi-Agent Systems
to automate complex business workflows. Apply
Prompt Engineering
and
Context Engineering
techniques to optimise AI performance and accuracy. Implement AI solutions using frameworks such as
LangChain ,
LangGraph , and
MCP . Integrate AI services and enterprise platforms through
REST APIs
and cloud-native architectures. Deliver scalable, secure, and reliable solutions using
Python ,
SQL ,
Git , and
CI/CD
practices. Test, evaluate, and continuously improve
LLM
and
AI Agent
performance, reliability, and safety. Collaborate with business, data, and engineering teams to drive AI adoption and innovation. Required Skills
AI ,
Generative AI (GenAI) ,
Large Language Models (LLMs) ,
Natural Language Processing (NLP) Prompt Engineering ,
Context Engineering AI Agents ,
Agentic AI ,
Multi-Agent Systems LangChain ,
LangGraph ,
Model Context Protocol (MCP) RAG ,
Embeddings ,
Vector Databases Python ,
SQL ,
REST APIs Git ,
CI/CD Cloud Platforms (Azure, AWS, or GCP) LLM & AI Agent Testing and Evaluation Desirable Skills
Knowledge Graphs Semantic Search Responsible AI Token Optimisation & Cost Management AI Evaluations (Evals) Re-ranking Techniques Caching Strategies Preferred Experience
Experience designing and implementing
Enterprise Knowledge Bases (EKBs) , AI-powered enterprise search, knowledge management, or intelligent retrieval platforms. Experience delivering AI solutions from prototyping through to production deployment in enterprise environments.
TPBN1_UKTJ
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