Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and build cutting-edge AI systems that transform recruitment experiences.
- Company: Join a forward-thinking tech company focused on innovative AI solutions.
- Benefits: Enjoy 29 days holiday, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with excellent mentorship and career advancement opportunities.
- Why this job: Make a real impact in the labour market with advanced AI technology.
- Qualifications: Strong software engineering skills in Python and cloud experience required.
The predicted salary is between 70000 - 90000 £ per year.
About our Marketplace Enablement Org and User Dialogue Team
Within Marketplace Enablement, we build the technology that helps candidates and recruiters find the right match. Our teams deliver data products, search and recommendations, and intelligent user dialogue capabilities using modern engineering practices, AI and cloud-native technology.
Within this org, our User Dialogue team is building the next generation of conversational and agentic AI experiences. This includes intelligent candidate engagement, personalised outreach, messaging journeys, and AI-powered systems that support users through complex recruitment journeys. By joining this team, you will be playing a vital role as together we reimagine the labour market to make it work for everybody.
The Role
We are recruiting for a Staff Software Engineer (AI) to help design, build and evolve production-grade agentic AI systems. This is a strategic, hands-on engineering leadership role focused on integrating Large Language Models into scalable, secure, reliable and observable architectures. This is an individual contributor leadership role with no direct line management responsibility.
You will help move our agentic AI capabilities beyond experimentation and into dependable products that operate safely and effectively at scale across our global marketplace. Working closely with software engineers, machine learning engineers, data scientists, product managers, analysts and technical leaders, you will shape how we build, test, deploy, monitor and govern AI-powered systems.
Success in this role will depend as much on influence and communication as on technical depth. You will need to create alignment across teams, explain complex concepts clearly, and help others make confident, pragmatic decisions.
Your responsibilities
- Design, architect and build agentic and LLM-powered systems within our AWS environment, with a focus on production readiness, reliability, security and scale.
- Provide technical leadership across teams, helping move AI capabilities from R&D and experimentation into maintainable, observable and operationally robust products.
- Work closely with product managers, engineers, machine learning engineers, data scientists and technical leaders to align technical decisions with user needs, business priorities and long-term platform direction.
- Define and improve engineering standards, reusable patterns, tools, templates and best practices for building agentic AI systems responsibly and consistently.
- Lead the implementation and deployment of systems at scale, ensuring strong approaches to testing, monitoring, evaluation, guardrails, observability and operational support.
- Communicate architectural choices, trade-offs and technical risks clearly to technical and non-technical stakeholders.
- Mentor and coach engineers, raising the engineering bar across design, delivery, code quality, security, maintainability and pragmatic technical decision-making.
- Contribute to tech-wide initiatives, collaborating across the organisation to promote standardisation, responsible AI practices and strong engineering design.
Qualifications
We are looking for a versatile Staff-level engineer with strong software engineering foundations and practical experience designing and delivering production-grade systems.
- Strong software engineering experience in Python and at least one of Java, TypeScript or .NET.
- Experience designing, building and operating distributed systems in AWS or comparable cloud platform.
- Practical experience integrating Large Language Models into production systems.
- Understanding of prompt orchestration, tool usage and LLM interaction patterns.
- Experience implementing state management, memory strategies, evaluation approaches and guardrails in AI systems.
- Experience with evaluation, observability and performance optimisation for LLM-powered systems.
- Experience using LLM APIs such as OpenAI, Bedrock or similar.
- Understanding of secure software development, data protection, compliance and enterprise architecture principles.
- Experience deploying and operating solutions on cloud platforms, preferably AWS.
- Excellent communication and influencing skills, with the ability to create shared understanding across technical and non-technical audiences.
- Experience mentoring engineers and raising standards across teams.
Benefits: 29 days holiday allowance +
Staff Software Engineer I in London employer: Cerebras
Contact Detail:
Cerebras Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Engineer I in London
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those related to AI and cloud tech. It’s a great way to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. Use mock interviews with friends or online platforms to get comfortable explaining your thought process.
✨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, you’ll be one step closer to joining our amazing team!
We think you need these skills to ace Staff Software Engineer I in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Staff Software Engineer role. Highlight your experience with AI systems, cloud platforms, and any relevant projects that showcase your skills in Python and LLM integration.
Showcase Your Communication Skills: Since this role involves influencing and aligning teams, don’t forget to demonstrate your communication prowess. Use clear examples in your application that show how you've effectively communicated complex ideas to both technical and non-technical audiences.
Highlight Leadership Experience: Even though this is an individual contributor role, we value leadership qualities. Share instances where you’ve led projects or mentored others, especially in engineering contexts, to show you can raise the bar for your peers.
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 shows you’re keen on joining our team!
How to prepare for a job interview at Cerebras
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and cloud platforms like AWS. Brush up on your experience with Large Language Models and be ready to discuss how you've integrated them into production systems.
✨Showcase Your Communication Skills
Since this role requires clear communication with both technical and non-technical stakeholders, prepare examples of how you've successfully explained complex concepts in the past. Think about times when you’ve influenced decisions or created alignment across teams.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills and technical leadership. Be ready to discuss specific scenarios where you’ve designed, built, or deployed AI systems, focusing on reliability, security, and scalability.
✨Demonstrate Your Mentorship Experience
Highlight your experience mentoring other engineers. Share specific instances where you’ve raised the engineering bar, improved code quality, or contributed to best practices in your previous roles. This will show your potential to lead and influence within the team.