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- Tasks: Design and deploy cutting-edge Generative AI solutions for enterprise clients.
- Company: Join a specialist data and AI consultancy driving innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with excellent career advancement opportunities.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: 1+ year experience in deploying GenAI applications and strong Python skills.
The predicted salary is between 60000 - 80000 £ per year.
Lynx Recruitment is partnering with a specialist data and AI consultancy to recruit an experienced AI Engineer to work on cutting-edge Generative AI and agentic AI solutions. Our client delivers data platforms, advanced analytics and AI/Machine Learning solutions that drive tangible business outcomes. The focus is on designing, deploying and operating production-grade GenAI and agentic systems on AWS, supporting organisations across multiple industries.
Role Overview
As an AI Engineer, you will design, develop and deploy production-ready Generative AI solutions for enterprise clients. You will be involved across the full lifecycle of GenAI products—from proof of concept through to scalable production deployment and monitoring. Working with modern LLMs, RAG architectures and agentic frameworks, you’ll collaborate with data engineers, solution architects and business stakeholders to deliver secure, cost-effective AI solutions on AWS.
Key Responsibilities
- Design and implement production GenAI applications using LLMs (e.g. Anthropic, AWS Bedrock models)
- Build and deploy RAG systems using vector databases and semantic search
- Develop agentic AI workflows using frameworks such as LangChain, LangGraph, CrewAI or similar
- Create effective prompt engineering strategies with appropriate guardrails for production systems
- Implement monitoring, evaluation and continuous improvement frameworks for GenAI applications
- Build and maintain CI/CD pipelines for testing, deployment and version control
- Work directly with client stakeholders to gather requirements, demonstrate solutions and iterate delivery
- Document architecture designs, decisions and best practices
Required Skills & Experience
- 1+ year hands-on experience deploying GenAI / LLM applications into production
- Experience with AWS services such as Lambda, SageMaker, Bedrock, S3, EC2 and ECS
- Strong Python development skills with modern AI/ML libraries
- Practical experience using at least one LLM API
- Solid understanding of prompt engineering, RAG architectures and vector databases
- Experience with LangChain, LangGraph, LlamaIndex or similar frameworks
- Familiarity with Git and CI/CD workflows
- Bachelor’s degree in Computer Science, Engineering or a related discipline (2.1 or above)
Highly Desirable
- Hands-on experience building agentic AI systems with planning, tool use and multi-step reasoning
- Experience fine-tuning or adapting LLMs for domain-specific use cases
- Familiarity with LLM evaluation frameworks (e.g. RAGAS, LangSmith)
- Knowledge of LLM security, hallucination mitigation and responsible AI practices
- Master’s degree in AI, Machine Learning, Data Science or a related field
AI Engineer employer: Lynx Recruitment
Contact Detail:
Lynx Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech space on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Generative AI and LLMs. We want to see what you can do, so make it easy for potential employers to check out your work.
✨Tip Number 3
Prepare for interviews by brushing up on common AI engineering questions and practical scenarios. We suggest doing mock interviews with friends or using online platforms to get comfortable with the process.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented AI Engineers 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 Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Engineer role. Highlight your experience with Generative AI, AWS services, and any relevant projects you've worked on. 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! Use it to explain why you're passionate about AI and how your background makes you a great fit for our team. Don't forget to mention specific technologies or frameworks you've worked with that relate to the job.
Showcase Your Projects: If you've got any personal or professional projects related to GenAI or LLMs, make sure to include them in your application. We love seeing practical examples of your work and how you've tackled challenges in the AI space.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're keen and ready to join the StudySmarter family!
How to prepare for a job interview at Lynx Recruitment
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially AWS services and LLMs. Brush up on your Python skills and be ready to discuss your hands-on experience with GenAI applications.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've designed or deployed AI solutions. Think about challenges you faced and how you overcame them, particularly in relation to prompt engineering and RAG architectures.
✨Understand the Business Impact
Be ready to explain how your work as an AI Engineer can drive tangible business outcomes. Research the company’s clients and industries they serve, and think about how your skills can add value to their operations.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the role and the company. Inquire about their current projects, team dynamics, or how they measure success in their AI initiatives. This demonstrates your enthusiasm and engagement.