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.
Key Responsibilities:
- 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.
Requirements:
- 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.
Technology Engineer 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 Technology 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 competitive benefits and a unique chance to contribute to impactful projects that shape the future of autonomous systems.
StudySmarter Expert Advice🤫
We think this is how you could land Technology Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 projects, especially those related to AI infrastructure and multi-modal systems. This will give potential employers a taste of what you can do beyond just your CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with AWS, Python, and building production systems. Practice common interview questions to boost your confidence!
✨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 an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Technology Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your strong Python skills and AWS infrastructure knowledge, especially with 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 production systems and how you've tackled challenges in previous roles.
Showcase Relevant Projects:If you've worked on multi-modal data pipelines or agentic AI systems, make sure to mention these projects. We want to see how you've applied your skills in real-world scenarios, so don't hold back!
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 us you’re keen to join 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 your experience with Python in detail. Bring examples of past projects where you’ve built production systems, not just prototypes. This will help demonstrate your capability to handle the technical demands of the role.
✨Think Like a Platform Engineer
Be ready to talk about schema design, API stability, and how you ensure backward/forward compatibility. This mindset is crucial for the role, so think of specific instances where you’ve had to consider these factors in your previous work.
✨Demonstrate Your Understanding of Multi-Modal Systems
Familiarise yourself with multi-modal data pipelines and be prepared to discuss any relevant experience you have with video, audio, or image processing. Showing that you can handle diverse data types will set you apart from other candidates.
