AI Enablement Engineer

Role Overview

• Design, build, and maintain AI-powered tools, automations, agent orchestration, and integrations that address real business problems identified through the AI enablement pipeline
• Translate requirements from the AI Enablement Manager/Specialist and department stakeholders into working technical solutions, scoping feasibility, selecting the right approach, and building to a standard that can be maintained and iterated upon
• Assess whether a business problem is best addressed through a custom build, configuration of an existing platform, or adoption of a third-party tool — and make a clear, reasoned recommendation before committing to a delivery approach
• Build and maintain LLM-based workflows and AI-assisted tools using the Foods Connected tooling ecosystem, including Claude, n8n, and connected enterprise platforms (HubSpot, Gong, Kantata , and others)
• Implement integration patterns between internal systems, AI services, and APIs — applying appropriate authorisation methods and data handling practices at every step
• Build with security and IT governance in mind from the outset: all integrations must be visible, documented, and aligned with IT oversight — not shadow infrastructure
• Support Work directly with business teams and department heads to understand operational problems, assess what is technically feasible , and explain clearly what can and cannot be done
• Support the AI Enablement Manager/Specialist in discovery sessions and workshops, providing the technical perspective needed to turn ideas into actionable requirements
• Communicate technical concepts and constraints in plain language — comfortable talking to colleagues who have no engineering background and adjusting accordingly
• Contribute to the qualification of inbound AI opportunities from a technical standpoint — assessing integration complexity, data requirements, security implications, and effort
• Lead the technical delivery of approved AI initiatives, from initial build through to rollout, user onboarding, and post-implementation iteration
• Work alongside Change and Transformation colleagues during rollouts, ensuring that what is built can be understood, used, and supported
• Build with observability in mind — instrument solutions so that adoption, usage, and errors can be tracked, and support the monitoring and reporting requirements of the AI Enablement function
• Gather and act on feedback from users post-launch, iterating on implementations to improve effectiveness and adoption
• Document technical designs, integration architectures, and operational runbooks to ensure continuity and enable handover where needed
• Work closely with IT and Security stakeholders to ensure all AI solutions are implemented within sanctioned infrastructure and comply with internal security standards
• Apply a security-first mindset to all integration work — handling authentication, data access, API security, and user permissions with appropriate care
• Contribute to the AI Governance Committee process from a technical standpoint where relevant — flagging risks, assessing vendor security posture, and supporting technical due diligence on new tools
• Maintain documentation of all AI integrations and automations in Confluence, ensuring the organisation has visibility of what is deployed and how it is governed
• Support the delivery of internal AI training and knowledge exchange sessions by providing technical depth and practical demonstrations
• Help build the technical AI literacy of colleagues across the organisation, able to show people how tools work, not just tell them
• Contribute to internal documentation, prompt libraries, and knowledge bases that make it easier for the wider team to work effectively with AI tools
• Bring ideas from the broader AI ecosystem, identifying relevant developments, tools, and patterns that could benefit Foods Connected's internal operations

Requirements

• Bachelor's degree or equivalent experience in Computer Science, Software Engineering, Information Systems, or a related field
• Demonstrable hands-on experience building with LLMs and modern AI tooling — this should be recent, practical experience, not theoretical familiarity
• A background that includes working directly with business users, support functions, or customer-facing teams, not purely isolated technical work
• Experience building integrations between enterprise systems and APIs, with sound working knowledge of authentication architectures and data flow
• Proven ability to take a problem from ambiguous brief to working solution in collaboration with non-technical stakeholders
• Hands-on experience with LLM APIs and concepts — including prompt engineering, RAG, function calling, agent frameworks, and tool use. Claude (Anthropic) experience is specifically valued
• Working knowledge of MCP (Model Context Protocol) and equivalent integration frameworks — comfortable connecting AI capabilities to enterprise systems in a governed way
• Experience with workflow automation and orchestration platforms — n8n experience is directly relevant; equivalent platforms (Zapier, Make, etc.) are acceptable where the underlying concepts are solid
• Understanding of web API patterns, authentication methods (OAuth, API keys, JWT), and the security considerations involved in connecting systems
• Strong enough engineering fundamentals to build reliable, maintainable solutions in Python or JavaScript/TypeScript — not required to be an expert in both, but solid in at least one
• Ability to read and reason about integration architectures, data schemas, and system interactions across a diverse enterprise tooling landscape

Tech Stack

• JavaScript
• Python
• TypeScript

Benefits

• Competitive Base Salary
• Generous Holiday Package
• 25 Days + 10 Public Holidays
• Private Medical, Dental & Vision
• Employee Wellness Program and Classes
• Flexible model of hybrid working