At a Glance
- Tasks: Build and ship innovative AI/ML features, from data ingestion to deployment.
- Company: Join a forward-thinking tech company leading in AI solutions.
- Benefits: Competitive pay, flexible work options, and opportunities for growth.
- Other info: Dynamic role with potential for contract extension and career advancement.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: Experience with 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.
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 in London employer: Queen Square Recruitment
As an AI Architect & Developer at our company, you will thrive in a dynamic and innovative environment that prioritises cutting-edge technology and collaborative teamwork. We offer competitive benefits, a strong commitment to employee growth through continuous learning opportunities, and a culture that embraces diversity and inclusion. Located in a vibrant tech hub, our workplace fosters creativity and provides access to industry-leading resources, making it an exceptional place for professionals seeking meaningful and rewarding careers in AI.
StudySmarter Expert Advice🤫
We think this is how you could land AI Architect & Developer in London
✨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 help you land that dream role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those involving LLMs and GenAI solutions. We want to see your hands-on experience, so make sure to highlight your best work!
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to AI architecture and development. We recommend practicing coding challenges and discussing your past projects to demonstrate your expertise.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AI Architect & Developer in London
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 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:This role involves working closely with various teams, so highlight any collaborative projects you've been part of. Share how you’ve translated complex architecture into practical solutions with stakeholders – we value teamwork at StudySmarter!
Apply Through Our Website:We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the process smoother for everyone involved!
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!
✨Showcase Your Technical Skills
Prepare to dive deep into your technical expertise, especially in Python, GCP, and CI/CD practices. Have examples ready that demonstrate your ability to build scalable AI solutions and how you've used tools like Docker and Kubernetes in your previous roles.
✨Understand the Business Context
Familiarise yourself with the company's goals and how your role as an AI Architect aligns with their vision. Be prepared to discuss how you can contribute to their long-term roadmap and ensure that your architectural designs meet business needs.
✨Emphasise Collaboration
Highlight your experience working with cross-functional teams. Discuss how you've collaborated with product managers, data scientists, and engineers to translate architecture into high-value solutions. This shows you're not just a techie but also a team player who understands the bigger picture.
