At a Glance
- Tasks: Design and build infrastructure for autonomous AI systems at production scale.
- Company: Innovative Series B company revolutionising decision-making for field workers.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic environment focused on innovation and career advancement.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: 4+ years in production systems, strong Python skills, and AWS expertise.
The predicted salary is between 70000 - 90000 £ per year.
Our client, a Series B company automating decision-making for field workers at scale, is looking for a Senior AI Platform Engineer to own the infrastructure layer enabling autonomous agents to operate reliably at production scale. You'll design and build the systems that allow their applied AI team to ship production LLM applications without breaking things. The focus is infrastructure engineering for AI systems — not traditional MLOps or feature engineering.
- Multi-modal data pipelines — Ingesting video, audio, and structured data at scale;
- Agentic orchestration on serverless AWS — Building Lambda + Step Functions infrastructure for autonomous workflows;
- Observability and guardrails — Implementing monitoring that catches when autonomous agents fail; tracking decision quality, tool-use patterns, and failure modes.
4+ years building production systems (not just experiments or prototypes); Strong Python skills; Deep AWS infrastructure knowledge — particularly serverless (Lambda, Step Functions, SQS, EventBridge); Hands-on experience with agentic AI systems, LLM orchestration frameworks (LangGraph, CrewAI, etc.); Platform engineer mindset — you think about schema design, API stability, backward/forward compatibility, and developer experience.
Experience with multi-modal systems (video, audio, or image processing); AWS Bedrock, SageMaker, or similar managed AI services; RAG pipelines, vector databases, or retrieval-augmented systems. You're not building features. You're building the infrastructure that enables autonomous decision-making at scale. This requires thinking like a platform engineer: How does data flow through the system without corruption? You've shipped production systems. You're comfortable with serverless, Python, and the AWS stack. You're not intimidated by agentic AI systems — you understand they're just orchestration patterns, and infrastructure principles remain the same.
Engineering Support Services in London employer: Wave Group
Join a forward-thinking Series B company that is revolutionising decision-making for field workers through cutting-edge AI technology. As a Senior AI Platform Engineer, you'll thrive in a dynamic work culture that prioritises innovation and collaboration, with ample opportunities for professional growth and development. Located in a vibrant tech hub, the company offers a unique chance to work on impactful projects while enjoying a supportive environment that values your contributions and encourages autonomy.
StudySmarter Expert Advice🤫
We think this is how you could land Engineering Support Services in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry 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 related to infrastructure engineering and AI systems. We want to see what you can do, so make it easy for us to find your best work.
✨Tip Number 3
Prepare for the interview like it’s game day! Research the company and their tech stack, and be ready to discuss how your experience with AWS and Python can help them build robust systems. We love candidates who come prepared!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for talent that can help us push the boundaries of AI infrastructure.
We think you need these skills to ace Engineering Support Services in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Senior AI Platform Engineer role. Highlight your experience with AWS, Python, and any relevant projects that showcase your skills in building production systems. We want to see how you fit into our vision!
Showcase Your Experience:Don’t just list your past jobs; tell us about the specific projects you've worked on that relate to infrastructure engineering for AI systems. We love seeing real-world examples of how you've tackled challenges and built reliable systems.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant to the role. We appreciate a well-structured application that gets straight to the point without fluff!
Apply Through Our Website:We encourage you to submit your application 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 Wave Group
✨Know Your Infrastructure Inside Out
Make sure you’re well-versed in the specific AWS services mentioned in the job description, like Lambda and Step Functions. Brush up on how these tools work together to support autonomous workflows, as this will show your potential employer that you can hit the ground running.
✨Showcase Your Production Experience
Prepare examples from your past work where you’ve built production systems, not just prototypes. Be ready to discuss challenges you faced and how you overcame them, especially in relation to multi-modal data pipelines or agentic AI systems.
✨Think Like a Platform Engineer
During the interview, demonstrate your platform engineer mindset by discussing schema design, API stability, and backward/forward compatibility. This will highlight your understanding of the infrastructure layer and how it supports the overall system.
✨Prepare for Technical Questions
Expect technical questions that dive deep into your Python skills and AWS knowledge. Practice coding problems related to infrastructure engineering and be ready to explain your thought process clearly, as communication is key in these roles.
