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For Companies At a Glance
- Tasks: Design and build real-world AI solutions that make a difference.
- Company: Join a tech-driven organisation focused on innovative AI applications.
- Benefits: Hybrid work, competitive pay, and potential for contract extension.
- Why this job: Turn AI ideas into impactful systems and shape the future of technology.
- Qualifications: Experience in AI engineering, strong Python skills, and cloud knowledge.
- Other info: Dynamic role with opportunities for growth in a fast-paced environment.
The predicted salary is between 48000 - 72000 £ per year.
Contract AI Engineer (Applied / Production AI)
Location: Reading / Hybrid
Contract: Initial 3-6 months (extension likely)
Start: ASAP
Overview
We are supporting a technology-driven organisation that is moving from AI experimentation into real production use cases. They are looking for a hands-on AI Engineer to design, build and deploy AI solutions that are secure, scalable and genuinely used by the business. This is a delivery-focused role - ideal for someone who enjoys turning AI ideas into working systems, not just proofs of concept.
Key Responsibilities
- Design and build production-ready AI solutions, with a strong focus on reliability and scalability
- Develop and deploy GenAI / LLM-based applications (e.g. copilots, internal tools, automation)
- Build and maintain AI services, APIs and integrations with existing platforms
- Implement data pipelines, embeddings, vector search and retrieval-augmented generation (RAG) patterns
- Work closely with engineering, product and business stakeholders to shape AI use cases
- Ensure solutions meet security, governance and performance requirements
- Contribute to best practice around AI engineering, MLOps and deployment patterns
Required Experience
- Proven experience as an AI Engineer / ML Engineer delivering AI into production
- Strong Python development skills
- Hands-on experience with LLMs (commercial and/or open-source)
- Experience building APIs and services around AI models
- Cloud experience (AWS, Azure or GCP)
- Familiarity with vector databases, embeddings and modern AI architectures
- Comfortable working in agile, fast-moving delivery environments
Nice to Have
- Experience with GenAI use cases (RAG, agents, copilots, document automation)
- Exposure to MLOps, CI/CD and monitoring of AI systems
- Experience in regulated or enterprise environments
- Consulting or client-facing delivery experience
What’s Attractive About This Role
- Focus on real AI delivery, not slideware or endless PoCs
- Opportunity to shape how AI is engineered and deployed
- Strong likelihood of extension based on delivery
- Hybrid working with a Reading base
AI Engineer Consultant employer: 83zero Limited
Contact Detail:
83zero Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer Consultant
✨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 that demonstrate your ability to build production-ready solutions. This will give you an edge and show employers you mean business.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with LLMs, APIs, and cloud platforms. Practice common interview questions to boost your confidence.
✨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 seen by the right people.
We think you need these skills to ace AI Engineer Consultant
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI engineering and production use cases. We want to see how you've turned ideas into real systems, so don’t hold back on those hands-on projects!
Showcase Your Skills: When writing your application, emphasise your Python skills and any experience with LLMs. We’re looking for someone who can build and deploy AI solutions, so let us know how you’ve done this in the past.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, especially when it comes to your experience with APIs, cloud platforms, and data pipelines. Make it easy for us to see why you’re a great fit!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and get the ball rolling on your journey with us at StudySmarter.
How to prepare for a job interview at 83zero Limited
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI engineering, especially around production-ready solutions. Be ready to discuss your hands-on experience with LLMs and how you've turned AI ideas into real systems. This is your chance to show off your Python skills and any cloud experience you have!
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles and how you tackled them. Think about examples where you designed and built scalable AI solutions or implemented data pipelines. This will demonstrate your ability to deliver in a fast-moving environment.
✨Understand the Business Side
Since this role involves working closely with product and business stakeholders, be ready to discuss how you've collaborated with different teams in the past. Highlight your experience in shaping AI use cases that meet security and performance requirements, as this will show you're not just technically savvy but also business-minded.
✨Ask Smart Questions
At the end of the interview, don’t forget to ask insightful questions about the company’s AI projects and their vision for the future. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you. Plus, it gives you a chance to demonstrate your understanding of MLOps and deployment patterns!
