At a Glance
- Tasks: Design and implement practical AI solutions from concept to deployment.
- Company: Dynamic tech company driving AI adoption across various sectors.
- Benefits: Competitive salary, quarterly bonuses, hybrid work, and career progression.
- Other info: Collaborative culture with opportunities for personal and professional growth.
- Why this job: Shape the future of AI in a fast-paced environment and make a real impact.
- Qualifications: Expertise in Python, AI/ML frameworks, and strong problem-solving skills.
The predicted salary is between 50000 - 60000 € per year.
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
- 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
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
Desirable Experience
- 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
Interested? Please click Apply Now!
AI Implementation Engineer in Warrington employer: Adria Solutions Ltd
Join a dynamic technology-led business in Manchester as an AI Implementation Engineer, where you will play a pivotal role in driving practical AI adoption across the organisation. With a strong focus on collaboration and innovation, the company offers a supportive work culture that encourages hands-on problem-solving and creativity, alongside competitive salaries, a quarterly bonus scheme, and hybrid working arrangements. This is an excellent opportunity for those looking to shape the future of AI within a growing business while enjoying significant career progression opportunities.
StudySmarter Expert Advice🤫
We think this is how you could land AI Implementation Engineer in Warrington
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those using Azure or machine learning. This gives you a tangible way to demonstrate your expertise and makes you stand out during interviews.
✨Tip Number 3
Prepare for hands-on assessments! Many tech roles, including AI Implementation Engineer positions, may require you to solve real problems on the spot. Brush up on your Python and relevant frameworks to ace these challenges.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining us. Plus, it’s a great way to ensure your application gets the attention it deserves from our hiring team.
We think you need these skills to ace AI Implementation Engineer in Warrington
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of AI Implementation Engineer. Highlight your experience with Python, Azure, and any relevant AI/ML frameworks. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for AI and how you've successfully implemented solutions in the past. Let us know why you're excited about joining our team at StudySmarter.
Showcase Your Problem-Solving Skills:In your application, give examples of how you've tackled challenges in previous roles. We love candidates who can demonstrate their ability to solve operational problems and deliver measurable impact.
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Adria Solutions Ltd
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI concepts, especially around Azure, LLMs, and machine learning frameworks. Be ready to discuss specific projects you've worked on and how you tackled challenges in building and deploying AI solutions.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your problem-solving abilities, particularly in operational contexts. Think about times when you’ve successfully implemented AI solutions that made a measurable impact, and be ready to share those stories.
✨Understand the Business Side
Since this role involves working closely with commercial teams, it’s crucial to understand how AI can drive business value. Familiarise yourself with the company’s current AI initiatives and think about how you can contribute to their goals.
✨Practice Collaboration Scenarios
You’ll need to work with both technical and non-technical stakeholders, so prepare for questions about collaboration. Think of instances where you’ve effectively communicated complex ideas to non-technical team members and how you ensured everyone was on the same page.
