At a Glance
- Tasks: Drive practical AI adoption and deliver solutions from concept to deployment.
- Company: A growing tech-led business focused on innovative AI solutions.
- Benefits: Competitive salary, quarterly bonuses, hybrid working, and career progression.
- Other info: Collaborative culture with opportunities to work on cutting-edge AI projects.
- Why this job: Shape the future of AI in a dynamic environment and make a real impact.
- Qualifications: Deep 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
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 robust 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! Get out there and connect with people in the AI field. Attend meetups, webinars, or industry events. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those using Azure or machine learning. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to discuss how you've tackled real-world challenges with AI solutions. Use examples that highlight your hands-on experience and collaboration with teams.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
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 AI Implementation Engineer role. Highlight your experience with Python, Azure, and any relevant AI/ML frameworks. We want to see how your skills align with what we're looking for!
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 this role and how you can contribute to our team.
Showcase Your Projects:If you've worked on any AI projects, make sure to include them! Whether it's building RAG pipelines or deploying models, we love seeing real-world examples of your work. It helps us understand your hands-on experience.
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get the best chance to showcase your skills. Don't miss out on this opportunity!
How to prepare for a job interview at Adria Solutions
✨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 those areas.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your problem-solving abilities, particularly in operational contexts. Think about how you've 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 success.
✨Practice Collaboration Scenarios
You’ll need to work with both technical and non-technical stakeholders, so practice explaining complex AI concepts in simple terms. Prepare for questions about how you’ve collaborated in the past and how you plan to engage with different teams.
