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 60000 - 80000 £ 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.
Engineer, R&D Tech 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 an Engineer in R&D Tech, you'll thrive in a collaborative and innovative work culture that prioritises employee growth and development, offering unique opportunities to work with advanced multi-modal data systems in a dynamic environment. With a strong focus on infrastructure engineering, you'll play a pivotal role in shaping the future of autonomous workflows while enjoying the benefits of a supportive team and a commitment to excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Engineer, R&D Tech 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 a big game day! Research the company, understand their tech stack, and be ready to discuss how your experience aligns with their needs. We love candidates who come in with knowledge about our mission.
✨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 fits our culture and values.
We think you need these skills to ace Engineer, R&D Tech in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the job description. Highlight your strong Python skills and AWS infrastructure knowledge, especially around serverless technologies like Lambda and Step Functions.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about building infrastructure for AI systems. Share specific examples of your experience with multi-modal data pipelines or agentic AI systems to show you understand the role.
Showcase Your Projects:If you've built production systems before, don’t hold back! Include links or descriptions of your past projects that demonstrate your hands-on experience with the technologies mentioned in the job description.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at Wave Group
✨Know Your Infrastructure Inside Out
Make sure you’re well-versed in the AWS services mentioned in the job description, especially Lambda and Step Functions. Brush up on how these tools can be used to build reliable systems for autonomous agents, as this will show your potential employer that you understand the core of what they need.
✨Showcase Your Python Skills
Prepare to discuss specific projects where you've used Python to build production systems. Be ready to explain your thought process behind schema design and API stability, as these are crucial for a platform engineer mindset. Having concrete examples will help you stand out.
✨Demonstrate Your Experience with Multi-Modal Systems
If you have experience with video, audio, or image processing, make sure to highlight it. Discuss any relevant projects where you ingested and processed multi-modal data at scale, as this aligns perfectly with what the company is looking for.
✨Think Like a Platform Engineer
During the interview, emphasise your understanding of how data flows through systems and the importance of observability. Be prepared to talk about how you’ve implemented monitoring solutions in past roles to catch failures and track decision quality, which is key for their infrastructure needs.
