At a Glance
- Tasks: Build and deploy cutting-edge AI/ML features and solutions.
- Company: Join a forward-thinking tech company leading in AI innovation.
- Benefits: Competitive pay, flexible work options, and opportunities for growth.
- Other info: Collaborative environment with potential for contract extension.
- Why this job: Be at the forefront of AI technology and make a real difference.
- Qualifications: Experience in LLM/GenAI, Python, and cloud technologies required.
The predicted salary is between 80000 - 100000 € per year.
Contract Length: 6 months (potential for extension)
What you'll do:
- Build and ship end-to-end AI/ML features, from data ingestion and training to deployment, MLOps workflows, CI/CD, and model versioning.
- Develop LLM/GenAI solutions: prompt engineering, RAG pipelines, embeddings, vector search, and inference optimisation (LoRA/PEFT, quantisation, GPU/TPU).
- Own observability across data, models, and prompts; run A/B tests, drive evaluation, and embed Responsible AI practices throughout.
What you'll need:
- Hands-on LLM/GenAI experience (Gemini or open source) including fine-tuning, RAG pipelines, prompt engineering, and graph-based workflows (ADK, MCP).
- Strong Python, API/microservices development, GCP (Vertex AI, BigQuery), CI/CD, and containerisation (Docker, Kubernetes).
Nice to have:
- ML frameworks (PyTorch, TensorFlow, Hugging Face), MLOps practices, API Gateway/ISTIO, IAM/data governance, Responsible AI standards.
AI Architect Position
Contract Length: 6 months (potential for extension)
What you'll do:
- Define and own the enterprise AI architecture vision, reference patterns, guidelines, reusable components, and long-term roadmap aligned to business goals, risk posture, and engineering standards across cloud and hybrid environments.
- Design secure, scalable AI solutions end-to-end: data ingestion, feature engineering, model training, inference, feedback loops, and MLOps/LLMOps pipelines with CI/CD, versioning, and reproducibility.
- Establish integration patterns (APIs, events, microservices) and agentic architectures (multi-agent orchestration, planner-executor, supervisor-worker) to embed AI capabilities into existing platforms and workflows.
- Operationalise observability, zero-trust security (BeyondCorp, IAM least-privilege), and model/LLM telemetry — ensuring audit-ready agent interactions, decision provenance, and AI quality metrics.
- Collaborate across product, data science, engineering, security, and business stakeholders to translate architecture into high-value solutions, selecting the right frameworks, cloud services, and orchestration tools throughout.
What you'll need:
- 7+ years designing enterprise AI/agentic architectures using multi-agent orchestration frameworks (LangGraph, Google ADK, MCP, A2A) with hands-on LLM, prompt engineering, and tool/function calling experience.
- Deep knowledge of RAG patterns, vector databases, embeddings, API-first integration, event-driven architectures, and GCP (or equivalent hyperscale).
Nice to have:
- MLOps/AgentOps, model governance, FCA/PRA compliance, regulated financial services, real-time and streaming inference, IAM/VPC security patterns.
AI Architect & Developer employer: Queen Square Recruitment
As an AI Architect & Developer at our innovative company, you will thrive in a dynamic work culture that prioritises collaboration and creativity. We offer competitive benefits, including flexible working arrangements and opportunities for professional development, ensuring you can grow your skills in cutting-edge AI technologies while contributing to impactful projects. Located in a vibrant tech hub, our workplace fosters a community of forward-thinkers dedicated to pushing the boundaries of AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land AI Architect & Developer
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and tech community, attend meetups, and connect 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/ML projects, especially those involving LLMs and GenAI solutions. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions related to AI architecture and development, and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you a leg up in the hiring process. Let’s get you that dream job!
We think you need these skills to ace AI Architect & Developer
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with LLM/GenAI solutions and MLOps practices. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Showcase Your Technical Skills:When detailing your experience, focus on your hands-on work with Python, API development, and cloud services like GCP. We love seeing specific examples of how you've built and shipped AI features, so be as detailed as possible!
Emphasise Collaboration:Since this role involves working with various teams, highlight any collaborative projects you've been part of. Share how you’ve worked with product, data science, and engineering teams to deliver high-value solutions – we value teamwork at StudySmarter!
Apply Through Our Website:We encourage you to submit your application through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Queen Square Recruitment
✨Know Your AI Stuff
Make sure you brush up on your hands-on experience with LLM/GenAI solutions. Be ready to discuss specific projects where you've implemented prompt engineering, RAG pipelines, or any graph-based workflows. The more detailed examples you can provide, the better!
✨Show Off Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common algorithms and data structures. Familiarise yourself with API/microservices development as well, as it’s crucial for this role.
✨Understand MLOps and CI/CD
Get comfortable with MLOps practices and CI/CD workflows. Be ready to explain how you've integrated these into your previous projects. Discussing your experience with containerisation tools like Docker and Kubernetes will also show that you’re well-versed in modern deployment strategies.
✨Collaboration is Key
This role involves working with various stakeholders, so be prepared to talk about your collaboration experiences. Share examples of how you've worked with product teams, data scientists, and engineers to translate architecture into high-value solutions. Highlight your communication skills and ability to work in a team.
