Areti Group | B Corp™
Artificial Intelligence Consultant
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AI Engineer (Enterprise AI Platforms & Architecture)
📍 London Hybrid (2 Days Onsite) - Ideally
📅 6 Month Contract
💷 Outside IR35
Overview
We are seeking an experienced AI Engineer to help design, build and scale enterprise-grade AI solutions within a complex technology environment.
This role is suited to someone who has moved beyond experimentation and prototypes and has successfully delivered AI platforms, products and capabilities into production at enterprise scale. You will play a key role in defining how AI is built, governed and operated across the organisation, working closely with engineering, architecture, security, platform, data and product teams. This is a highly influential role requiring a blend of hands-on engineering capability, enterprise architecture exposure and practical experience implementing AI solutions in production environments.
The Opportunity
You will help shape the future AI engineering capability of the organisation by defining the frameworks, patterns, standards and governance required to safely scale AI across multiple business and technology domains.
The successful candidate will understand not only how to build AI-powered solutions, but how to operate them within enterprise environments where security, compliance, reliability, cost management and governance are critical.
Key Responsibilities
- Design and implement enterprise-scale AI solutions and platforms using modern LLM architectures.
- Define AI architecture patterns, standards and engineering best practices.
- Develop AI application frameworks, reusable services and shared platform capabilities.
- Partner with Engineering, Architecture, Security and Data teams to establish enterprise AI operating models.
- Build robust governance, evaluation and quality assurance processes for AI-generated outputs and code.
- Design secure and compliant AI solutions suitable for regulated environments.
- Create scalable approaches to context management, retrieval strategies and knowledge integration.
- Establish monitoring, observability and performance management frameworks for AI services.
- Drive adoption of AI-enabled engineering practices across development teams.
- Optimise AI solutions for reliability, scalability, latency and cost efficiency.
- Provide technical leadership and guidance on enterprise AI strategy and implementation.
- Influence architectural decisions and support the evolution of AI capability across the wider technology function.
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Required Experience
We are looking for a proven AI practitioner with significant experience delivering AI solutions into production within enterprise environments.
You should demonstrate experience in:
Enterprise AI & Architecture
- Designing and implementing enterprise AI solutions and platforms.
- Working within large-scale enterprise environments with multiple stakeholders.
- Defining AI architecture, technical standards and governance frameworks.
- Collaborating with Architecture, Security, Platform and Engineering teams.
- Establishing controls, guardrails and risk management approaches for AI systems.
- Designing AI solutions for regulated or compliance-sensitive organisations.
AI Engineering
- Building and deploying production-grade LLM-powered applications.
- Agentic AI workflows, tool calling and autonomous execution frameworks.
- Retrieval Augmented Generation (RAG) and context engineering.
- Structured outputs, orchestration and workflow automation.
- Multi-agent architectures and AI-powered development environments.
- Evaluation frameworks, testing strategies and AI quality measurement.
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Production Operations
- Production monitoring and observability.
- AI performance optimisation and operational support.
- Cost management, token optimisation and model selection strategies.
- Managing reliability, latency, scalability and failure handling.
- Diagnosing retrieval, reasoning and generation issues in production environments.
Essential Attributes
- Experience building AI solutions beyond proof of concept stage.
- Strong architecture and solution design capability.
- Ability to communicate effectively with technical and non-technical stakeholders.
- Experience working across multiple teams to deliver enterprise outcomes.
- Comfortable operating in fast-paced environments with evolving AI technologies.
- Strong understanding of enterprise concerns including security, governance, compliance and operational risk.
Highly Desirable
- Experience building internal AI developer platforms.
- Model Context Protocol (MCP) implementation experience.
- AI infrastructure and platform engineering experience.
- Experience establishing enterprise AI adoption programmes.
- Experience creating governance frameworks for AI-assisted software engineering.
- Background within financial services, consulting, regulated industries or large-scale enterprise organisations.
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