Manchester Digital
AI Implementation Engineer
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A growing technology-led business is looking to hire an AI Implementation Engineer to help drive practical AI adoption across multiple areas of the organisation.
This is a hands-on role focused on delivering AI solutions from concept through to live deployment and business adoption. Working within IT and closely alongside operational and commercial teams, you will build and implement practical AI use cases using Azure, LLMs, machine learning, and AI agents — ensuring solutions are secure, integrated, scalable, and actively used across the business.
The organisation is already exploring a broad range of AI initiatives and is looking for someone capable of getting hands-on with implementation, working collaboratively with existing technical teams, and helping shape the future AI capability of the business.
This role would suit someone who enjoys building practical AI solutions, solving operational problems, and delivering measurable business impact in a fast-moving environment.
Role Purpose
Hands-on role responsible for delivering AI solutions from concept through to live deployment and business adoption.
Working within IT and closely with business teams, you will build and implement practical AI use cases using Azure, LLMs, ML, and AI agents — ensuring they are secure, integrated, scalable, and actively used.
Key Responsibilities
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- Design and build high-performing AI models tailored to specific business needs
- Lead rapid prototyping initiatives through to production delivery
- Work directly with the IT Infrastructure team to deploy AI models into production environments
- Ensure solutions use Private Endpoints and meet enterprise-grade security standards
- Work with operational and business teams to embed AI tools into day-to-day workflows
- Drive adoption and ensure teams are actively using implemented AI solutions
- Set up automated evaluation and monitoring frameworks for production AI environments, including hallucination detection, drift monitoring, and latency tracking (GenAIOps)
- Ensure AI solutions integrate securely with existing systems, data platforms, and APIs
- Collaborate with commercial stakeholders to assess project viability and business value before implementation
- Measure and track project impact, including efficiency gains, time savings, automation improvements, and quality outcomes
- Work closely with IT, development, and leadership teams to identify and prioritise AI opportunities across the organisation
Essential
Required Experience
- Deep expertise in Python and relevant AI/ML frameworks and SDKs
- Proven experience building RAG pipelines that operate effectively in production environments
- Hands-on experience with model packaging, deployment, and production AI workflows
- Strong understanding of enterprise infrastructure concepts including VNets, Entra ID, API Gateways, and secure integrations
- Experience working with at least one major enterprise AI cloud platform (Azure preferred)
- Strong SQL skills and experience working with both structured and unstructured data
- Experience building AI agents, workflow automation, and tool/API integrations
- Strong understanding of AI implementation, deployment, and operationalisation
- Ability to work closely with technical and non-technical stakeholders
- Strong problem-solving and communication skills
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Desirable
- Experience with LLMOps / GenAIOps tooling and monitoring frameworks
- Exposure to OCR, computer vision, voice AI, or conversational AI solutions
- Experience working in operational, retail, automotive, or customer-focused businesses
- Familiarity with AI governance, security, and scalability best practices
- Experience helping shape or build internal AI capabilities within a business
Salary & Benefits
- Competitive salary depending on experience
- Quarterly bonus scheme
- Hybrid working arrangements — 3 days office / 2 days remote
- Opportunity to shape AI capability within a growing business
- Strong long-term career progression opportunities
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