AI Delivery Lead — Production ML & Strategy (Hybrid)

Adria Solutions Ltd.; Manchester; Hybrid; GBP 60,000 - 85,000; Full time

Benefits offered by this job

Quarterly bonus

Hybrid working

Career progression

Job summary

Adria Solutions Ltd. in Manchester is seeking an AI Implementation Engineer to lead production AI delivery, bridging data science with enterprise infrastructure and business outcomes. This hybrid role combines hands-on development with strategic leadership.

You will design AI strategies, build LLM applications, RAG pipelines, and collaborate with data engineering and IT teams to deploy secure, scalable AI in enterprise environments.

Qualifications

• Experience delivering production AI solutions.
• Strong Python programming skills.
• Proven ability to lead AI initiatives.
• Experience with Azure AI services.
• Ability to work across IT and business teams.

Responsibilities

• Define AI strategy and identify high-value opportunities.
• Lead AI projects from concept to production deployment.
• Design and develop AI/ML solutions using Azure and modern AI tech.
• Build production-ready LLM apps, RAG pipelines and AI agents.
• Work with Data Engineering to prepare structured/unstructured data.
• Collaborate with Infra teams to deploy secure, scalable AI.
• Embed AI tools into workflows and drive adoption.
• Establish monitoring, governance for production AI environments.
• Measure impact by business value and automation gains.
• Provide technical leadership across AI initiatives.

Skills

Data Science

Machine Learning

LLMs

RAG solutions

Python

Data engineering

Enterprise infrastructure

Stakeholder management

Strategic AI deployment

Tools

Azure AI services

Python SDKs

Job description

Adria Solutions Ltd. in Manchester is seeking an AI Implementation Engineer to lead production AI delivery, bridging data science with enterprise infrastructure and business outcomes. This hybrid role combines hands-on development with strategic leadership.

You will design AI strategies, build LLM applications, RAG pipelines, and collaborate with data engineering and IT teams to deploy secure, scalable AI in enterprise environments.