At a Glance
- Tasks: Design and deliver innovative AI solutions for public sector and enterprise clients.
- Company: Join a forward-thinking tech company focused on AI transformation.
- Benefits: Competitive salary, health benefits, remote work options, and career development opportunities.
- Other info: Dynamic team environment with strong values of teamwork and mutual success.
- Why this job: Be at the forefront of AI technology and make a real difference in digital transformation.
- Qualifications: 2+ years in AI engineering or software development with a focus on GenAI and LLMs.
The predicted salary is between 60000 - 80000 € per year.
We're hiring an AI Engineer to design and deliver production-grade GenAI and Agentic AI solutions across our public sector and enterprise clients. The successful candidate will work across AI Engineering disciplines including Generative AI, Agentic AI, Large Language Models and LLMOps as part of our growing AI Engineering team. You will work with architects, engineers and business stakeholders to deliver cloud-based AI solutions using GenAI and agentic systems, helping clients unlock data value, automate complex processes and drive digital transformation. Due to the nature of this role, successful candidates may need to undergo security clearance. To be eligible you must have lived in the UK for at least 5 consecutive years.
Responsibilities
- Deploy, fine-tune and monitor Generative AI models and Agentic AI systems for enterprise use cases.
- Develop and implement Retrieval-Augmented Generation (RAG) pipelines and advanced prompt and context engineering strategies.
- Design and implement multi-agent systems using orchestration frameworks such as CrewAI, Semantic Kernel or LangGraph.
- Integrate Agentic AI into business workflows and collaborate with data engineers to bring agentic capabilities to production.
- Implement LLM evaluation pipelines to assess output quality, accuracy and safety.
- Apply responsible AI principles including fairness, transparency and auditability, particularly for regulated public sector environments.
- Apply AI safety, guardrails and output validation controls to ensure robust, compliant production deployments.
- Evaluate and recommend emerging GenAI tools and agentic frameworks for client applicability, driving innovation within the team.
About you
- 2+ years’ experience in AI engineering, software development or data science, with a strong recent focus on GenAI and LLMs.
- Hands-on experience with GenAI orchestration frameworks and cloud platforms, including Azure AI Foundry, CrewAI, LangChain, Semantic Kernel, Hugging Face and Azure ML Studio.
- Strong capability in prompt and context engineering, RAG pipeline design, and LLMOps, including tooling such as PromptFlow, LangSmith, prompt versioning and LLM cost management.
- Experience working with Azure data and analytics services, including Data Factory, Data Lake, Synapse Analytics and Azure SQL Database.
- Strong programming skills (Python, C# or similar), with experience using Azure DevOps/GitHub CI/CD, and working across the software development lifecycle, including access control, audit logging, documentation, knowledge transfer and training.
- Knowledge and experience of the following would be advantageous:
- Experience deploying AI solutions on Azure, including Azure OpenAI, Azure AI Foundry and Azure ML Studio, with familiarity using Microsoft Copilot Studio.
- Experience with ML and AI engineering toolchains, including MLflow, Databricks CLI, automated retraining pipelines, drift detection, MLSecOps, and LLM evaluation frameworks (e.g. RAGAS, DeepEval) alongside AI safety tooling (Azure Content Safety, Guardrails AI).
- Experience with Infrastructure as Code (IaC) using Terraform, Bicep or ARM Templates to provision, manage and version cloud resources.
- Familiarity with agentic AI and ML technologies, including MCP (Model Context Protocol), tool-use patterns, Computer Vision (OCR/object recognition), core ML frameworks (TensorFlow, PyTorch, Scikit-learn).
What we look for in our people
- Strong alignment with FSP values and ethos.
- Commitment to teamwork, quality and mutual success.
- Proactivity with an ability to operate with pace and energy.
- Strong communication and interpersonal skills.
- Dedication to excellence and quality.
Equal and Fair Opportunity
FSP is an equal opportunity employer and we welcome applications from all suitable candidates. We consider all applicants for employment regardless of age, disability, sexual orientation, gender identity, family or parental status, race, colour, nationality, ethnic or national origin, religion or belief. We endeavour to always provide fair opportunity for applicants to showcase themselves in the best way possible during any interviews or meetings. If you require any adjustments for a call or in-person meeting, please let us know.
Artificial Intelligence Engineer employer: FSP
As an AI Engineer at our company, you will be part of a dynamic and innovative team dedicated to delivering cutting-edge AI solutions for public sector and enterprise clients. We foster a collaborative work culture that values teamwork, quality, and mutual success, while providing ample opportunities for professional growth and development in the rapidly evolving field of AI. Located in the UK, we offer a supportive environment that prioritises fairness and inclusivity, ensuring that all employees can thrive and contribute meaningfully to transformative projects.
StudySmarter Expert Advice🤫
We think this is how you could land Artificial Intelligence Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI space, attend meetups or webinars, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Generative AI and LLMs. This gives you a chance to demonstrate your hands-on experience and creativity, making you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI engineering questions and scenarios. Practice explaining your thought process when deploying AI solutions and how you tackle challenges. Confidence and clarity can make all the difference!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team and contributing to exciting AI projects.
We think you need these skills to ace Artificial Intelligence 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, LLMs, 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 you can contribute to our team. Be sure 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 AI, make sure to include them in your application. We love seeing practical examples of your work, especially if they involve cloud-based solutions or innovative AI applications.
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. Plus, it gives you a chance to explore more about StudySmarter and what we do!
How to prepare for a job interview at FSP
✨Know Your AI Stuff
Make sure you brush up on your knowledge of Generative AI, Agentic AI, and Large Language Models. Be ready to discuss specific projects you've worked on, especially those involving cloud platforms like Azure. This will show that you’re not just familiar with the concepts but have practical experience too.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex problems in previous roles. Think of examples where you deployed AI solutions or developed RAG pipelines. Highlight your thought process and the impact of your solutions on the business.
✨Get Familiar with the Tools
Since the role involves using various orchestration frameworks and tools, make sure you know your way around them. If you’ve used Azure AI Foundry, CrewAI, or similar tools, be ready to share your experiences and any challenges you faced while using them.
✨Emphasise Teamwork and Communication
This role requires collaboration with architects, engineers, and business stakeholders. Be prepared to discuss how you’ve worked in teams before, your communication style, and how you ensure everyone is on the same page during projects.
