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For Companies At a Glance
- Tasks: Design and build AI systems that enhance engineering workflows and deliver measurable impact.
- Company: Join Glassbox, a leader in shaping digital customer experiences with innovative AI solutions.
- Benefits: Competitive salary, health benefits, remote work options, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and real-world impact.
- Why this job: Be at the forefront of AI technology, transforming how engineering teams operate in the digital age.
- Qualifications: 2-5+ years in backend engineering, experience with LLM-based agents, and strong coding skills.
The predicted salary is between 60000 - 80000 £ per year.
Glassbox's mission is to reveal the insights that empower organizations to deliver exceptional digital customer experiences. Glassbox is a leading force in shaping digital experiences. It helps organizations uncover digital issues, boost conversion rates, enhance accessibility, prevent fraud, and more. Leveraging AI-driven customer intelligence, Glassbox enables enterprises to deliver secure, proactive, and preventative digital experiences. Its solutions are trusted by highly regulated organizations, including SoFi, Cal, and many others. We are growing and have been recognized by G2 as one of 2024's Top 50 Software Companies in the world.
We are building an AI-native R&D platform that transforms how engineering teams operate. Our vision is to move from reactive workflows to intelligence-driven systems, where AI agents are embedded across the entire software development lifecycle – from code to production.
The Role
We are looking for a hands-on AI Agent Engineer to design and build production-grade AI systems that integrate deeply into engineering workflows. This is not a research role and not a prompt-engineering role. You will build real systems that:
- Are used daily by engineers
- Run independently and take action
- Deliver measurable impact on speed, quality, and reliability
What You'll Do
Design and build AI agents that:
- Assist engineers in real-time (copilot mode)
- Operate autonomously and take actions (self-sufficient mode)
Develop end-to-end agent workflows across systems such as:
- CI/CD pipelines
- Code repositories
- Observability and monitoring tools
- Support and ticketing systems
Build core components:
- RAG pipelines (retrieval, embeddings, vector databases)
- Tool-integrated agents (APIs, services, workflows)
- Agent orchestration, memory, and state management
Turn LLM capabilities into production-grade systems by:
- Handling failures, retries, and edge cases
- Managing latency, cost, and scalability
- Implementing observability (e.g., Langfuse or similar)
Work closely with engineering teams to ensure:
- Real adoption
- Seamless integration into workflows
- Balance between autonomy and human control
Requirements
- Strong backend or platform engineering experience (2–5+ years)
- Proven experience building and deploying LLM-based agents in production
- Hands-on experience with:
- LangChain, LangGraph, or similar frameworks
- LLM APIs (OpenAI, Anthropic, etc.)
- RAG systems (vector DBs, embeddings, retrieval pipelines)
- Tool-based agents (APIs, workflows, automation)
Nice to Have
- Experience building multi-agent or autonomous systems
- Experience designing human-in-the-loop workflows
- Background in DevOps, CI/CD, QA, or DevEx platforms
- Experience with event-driven systems (Kafka, queues)
- Experience integrating AI into:
- Code review
- Testing / QA
- Incident analysis
Who You Are
- A builder – you ship systems end-to-end
- You think in systems and workflows, not just prompts
- You are comfortable going from idea to production
- You care about impact, reliability, and real-world usage
Why Join Us
You’ll be building the foundation of an AI-native engineering platform, where:
- Agents are first-class components across R&D
- Systems are autonomous, connected, and continuously improving
- Engineering teams are augmented – not replaced – by AI
This is an opportunity to shape how modern engineering organizations operate in the AI-first era.
AI Platform Engineer - Autonomous Agents in Norwich employer: Glassbox
Contact Detail:
Glassbox Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Platform Engineer - Autonomous Agents in Norwich
✨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 or GitHub repository showcasing your projects, especially those related to AI systems and workflows. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios relevant to AI platform engineering. Mock interviews with friends or using online platforms can help you feel more confident and ready to impress.
✨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, it shows you’re genuinely interested in joining our team at Glassbox.
We think you need these skills to ace AI Platform Engineer - Autonomous Agents in Norwich
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the AI Platform Engineer role. Highlight your experience with LLM-based agents and any relevant projects you've worked on. We want to see how your skills align with our mission at Glassbox!
Showcase Your Technical Skills: Don’t hold back on showcasing your coding skills in TypeScript or Python. Include specific examples of how you've built and deployed systems, especially those that integrate AI into workflows. This is your chance to shine!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to read through your experiences and achievements. We appreciate a well-structured application!
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 Glassbox
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like LangChain, LangGraph, and LLM APIs. Brush up on your coding skills in TypeScript or Python, as you'll likely be asked to demonstrate your knowledge during the interview.
✨Showcase Real-World Applications
Prepare examples of how you've built and deployed AI systems in production. Be ready to discuss specific projects where you’ve integrated AI into workflows, especially focusing on measurable impacts on speed, quality, and reliability.
✨Understand the Role of Autonomy
Since the role involves designing autonomous systems, think about how you can balance autonomy with human control. Be prepared to discuss your approach to building systems that operate independently while still being user-friendly.
✨Ask Insightful Questions
Prepare thoughtful questions about Glassbox's vision for AI integration in engineering workflows. This shows your genuine interest in the company and helps you understand how you can contribute to their mission of enhancing digital customer experiences.