AI Consultant

Reed; Sheffield; On-site; GBP 70,000 - 110,000; Full time

Job summary

Reed in Sheffield seeks an AI Engineer to design, implement, and manage enterprise AI platforms, agents, and supporting infrastructure. You will deliver scalable AI workloads, integrate with business systems, and produce architecture documentation to drive governance and best practices.

You will work across cloud and on‑prem environments, focusing on secure, scalable solutions including RAG apps and multi‑agent orchestration.

Qualifications

• Proven experience designing, building, and deploying AI/ML solutions within enterprise environments.

Responsibilities

• Design, implement, and maintain enterprise AI infrastructure across cloud and on-premise environments.
• Develop scalable architectures for AI workloads, including model hosting, vector databases, orchestration layers, APIs, and data pipelines.
• Integrate AI platforms with business-critical systems, data platforms, collaboration tools, and operational applications.
• Produce and maintain architecture documentation, operational procedures, and technical standards.
• Design, develop, and manage AI agents, copilots, and workflow automation solutions.
• Build Retrieval-Augmented Generation (RAG) applications leveraging internal business data.
• Develop intelligent assistants supporting operational, engineering, customer service, and business functions.
• Implement multi-agent workflows and orchestration frameworks.
• Monitor and optimise AI solution performance, reliability, security, and cost efficiency.
• Ensure AI solutions align with security, governance, and compliance requirements.
• Support data governance, privacy, risk management, and lifecycle policies for AI-enabled systems.
• Maintain standards and documentation relating to AI usage, access control, and governance frameworks.
• Contribute to responsible AI practices and organisational AI governance initiatives.
• Partner with teams across the organisation to identify and prioritise AI opportunities.
• Support user adoption, training, and change management activities.
• Translate complex technical concepts into clear business language for non-technical stakeholders.
• Act as a trusted advisor on AI technologies and best practices.

Skills

Python

REST APIs

Docker

Kubernetes

Vector databases

Embeddings

RAG architectures

LLM orchestration

AWS

Microsoft 365

SQL databases

Tools

Docker

Kubernetes

Job description

AI Engineer

Sheffield

Permanent

The Role

As an AI Engineer, you will be responsible for the design, implementation, and ongoing management of AI platforms, intelligent agents, and supporting infrastructure. You'll combine hands‑on technical delivery with strategic input, ensuring AI solutions are scalable, secure, and aligned with organisational objectives.

Key Responsibilities

AI Platform & Infrastructure

• Design, implement, and maintain enterprise AI infrastructure across cloud and on-premise environments.
• Develop scalable architectures for AI workloads, including model hosting, vector databases, orchestration layers, APIs, and data pipelines.
• Integrate AI platforms with business-critical systems, data platforms, collaboration tools, and operational applications.
• Produce and maintain architecture documentation, operational procedures, and technical standards.

AI Agents & Automation

• Design, develop, and manage AI agents, copilots, and workflow automation solutions.
• Build Retrieval-Augmented Generation (RAG) applications leveraging internal business data.
• Develop intelligent assistants supporting operational, engineering, customer service, and business functions.
• Implement multi-agent workflows and orchestration frameworks.
• Monitor and optimise AI solution performance, reliability, security, and cost efficiency.

Governance & Compliance

• Ensure AI solutions align with security, governance, and compliance requirements.
• Support data governance, privacy, risk management, and lifecycle policies for AI-enabled systems.
• Maintain standards and documentation relating to AI usage, access control, and governance frameworks.
• Contribute to responsible AI practices and organisational AI governance initiatives.

Stakeholder Engagement

• Partner with teams across the organisation to identify and prioritise AI opportunities.
• Support user adoption, training, and change management activities.
• Translate complex technical concepts into clear business language for non-technical stakeholders.
• Act as a trusted advisor on AI technologies and best practices.

About You

Essential Skills & Experience

• Proven experience designing, building, and deploying AI/ML solutions within enterprise environments.
• Strong Python development skills.
• Experience integrating and consuming REST APIs.
• Hands‑on experience with Docker and Kubernetes.
• Knowledge of vector databases, embeddings, RAG architectures, and LLM orchestration frameworks.
• Experience with cloud technologies, networking, identity and access management, and security controls.
• Experience integrating AI solutions with Microsoft 365 technologies, collaboration platforms, and SQL‑based databases.
• Strong experience working within AWS environments and services.

Desirable Experience

• AI governance and responsible AI frameworks.
• MLOps and LLMOps tools and methodologies.
• Prompt engineering and model fine‑tuning.
• Agentic AI frameworks such as LangGraph, AutoGen, or CrewAI.
• AI orchestration platforms such as n8n or similar technologies.
• Knowledge graph technologies.
• Data lake and analytics platforms.
• Experience supporting organisation‑wide AI adoption programmes.