AI Engineer

Halian | Managed Services, Recruitment Agency & Contract Staffing; Reading; Hybrid; GBP 85,000 - 120,000; Full time

Benefits offered by this job

Bonus

Pension

Private Healthcare

Hybrid Working

Flexi-time

Learning & Development Budget

Life Assurance

Job summary

Halian seeks an experienced AI Engineer to design, build, and deploy advanced AI capabilities for a large-scale enterprise software platform. You will work with LLMs, Generative AI, and Agentic AI, delivering production-ready features within a modern, collaborative engineering environment.

The role emphasizes multi-agent workflows, AI orchestration, RAG with vector databases, and real-time AI pipelines. Strong cloud deployment skills and a passion for learning emerging AI technologies are

Qualifications

• 5+ years of commercial software development experience.
• Proven experience building and deploying production-grade LLM applications.
• Commercial experience developing Generative AI and Agentic AI solutions.
• Experience with Retrieval-Augmented Generation (RAG) architectures and vector databases.
• Experience with AI orchestration frameworks such as LangChain, Semantic Kernel, AutoGen, or similar.
• Experience designing, evaluating, and optimising prompts for Large Language Models.
• Experience deploying AI solutions into cloud environments, ideally Azure.
• Strong understanding of software engineering best practices and scalable system design.

Responsibilities

• Designing and developing AI-powered features for a large-scale enterprise software platform.
• Building and deploying LLM, Generative AI, and Agentic AI solutions into production environments.
• Developing multi-agent workflows to automate complex business processes.
• Implementing AI orchestration using modern frameworks and the Model Context Protocol (MCP).
• Designing and implementing Retrieval-Augmented Generation (RAG) solutions using vector databases.
• Building scalable AI services and data processing pipelines using Python.
• Developing real-time AI applications, including streaming and speech-enabled solutions.
• Integrating AI capabilities into existing backend and frontend systems.
• Optimising prompts and AI workflows to improve accuracy, reliability, and performance.
• Collaborating with engineering, product, and domain experts to deliver impactful AI solutions.
• Researching, evaluating, and implementing emerging AI technologies and best practices.

Skills

5+ years experience

LLM/Generative AI

Agentic AI

RAG architectures

AI orchestration frameworks

prompt engineering

Azure / cloud deployment

scalable system design

Tools

Pinecone/Weaviate/FAISS

OpenAI and other foundation models

Job description

BENEFITS – Bonus, Pension, Private Healthcare, Hybrid Working, Flexi-time, Learning & Development Budget, Life Assurance etc.

We are an innovative UK technology company developing cutting-edge software solutions for the healthcare sector. As part of our continued investment in Artificial Intelligence, we are expanding our AI Engineering team to build intelligent solutions that improve user experiences, automate complex workflows, and solve real-world challenges.

We are looking to hire an experienced AI Engineer to design, build, and deploy advanced AI solutions across a modern software platform. You will work with Large Language Models (LLMs), Generative AI, Agentic AI, and real-time AI technologies, helping to deliver production-ready AI capabilities within a collaborative engineering environment.

The AI Engineer MUST have:

• 5+ years of commercial software development experience
• Proven experience building and deploying production-grade LLM applications
• Commercial experience developing Generative AI and Agentic AI solutions
• Experience with Retrieval-Augmented Generation (RAG) architectures and vector databases
• Experience with AI orchestration frameworks such as LangChain, Semantic Kernel, AutoGen, or similar
• Experience designing, evaluating, and optimising prompts for Large Language Models
• Experience deploying AI solutions into cloud environments, ideally Azure
• Strong understanding of software engineering best practices and scalable system design

The AI Engineer will ideally have the following attributes:

• Experience building multi-agent workflows and autonomous AI systems
• Knowledge of the Model Context Protocol (MCP) and AI integration patterns
• Experience with vector databases such as Pinecone, Weaviate, FAISS, or Azure AI Search
• Experience working with OpenAI and other leading foundation models
• Knowledge of real-time AI pipelines, including speech-to-text and streaming AI applications
• Experience with technologies such as Pipecat, Daily, Deepgram, or similar real-time AI frameworks would be advantageous
• Experience integrating AI capabilities into enterprise backend and frontend applications
• Strong problem-solving skills with the ability to deliver practical, production-ready AI solutions
• A passion for learning emerging AI technologies and rapidly adopting new frameworks and tools
• Excellent communication skills and the ability to collaborate with cross-functional teams

The AI Engineer role will involve:

• Designing and developing AI-powered features for a large-scale enterprise software platform
• Building and deploying LLM, Generative AI, and Agentic AI solutions into production environments
• Developing multi-agent workflows to automate complex business processes
• Implementing AI orchestration using modern frameworks and the Model Context Protocol (MCP)
• Designing and implementing Retrieval-Augmented Generation (RAG) solutions using vector databases
• Building scalable AI services and data processing pipelines using Python
• Developing real-time AI applications, including streaming and speech-enabled solutions
• Integrating AI capabilities into existing backend and frontend systems
• Optimising prompts and AI workflows to improve accuracy, reliability, and performance
• Collaborating with engineering, product, and domain experts to deliver impactful AI solutions
• Researching, evaluating, and implementing emerging AI technologies and best practices