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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, private healthcare, and a hybrid working model.
- Other info: Collaborative environment with opportunities for mentorship and career growth.
- Why this job: Make a real impact in the labour market with your engineering skills.
- Qualifications: Strong software engineering experience, especially in Python and cloud platforms.
The predicted salary is between 60000 - 80000 £ 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 + bank holidays
- Private medical and dental healthcare
- Matching pension contribution of 4 or 5% (after 3 years of service up to 10%)
- 24/7 Employee Assistance Programme
- Life Assurance Cover
- Cycle to work scheme
- Hybrid working model (3 days working from the office)
- Volunteering days and you can bring your dog to the office on Mondays and Fridays!
Our commitment
Equal opportunities are important to us. We believe that diversity and inclusion at The Stepstone Group are critical to our success as a global company, so we want to recruit, develop, and keep the best talent. We encourage applications from everyone, regardless of background, gender identity, sexual orientation, disability status, ethnicity, belief, age, family or parental status, and any other characteristic.
Staff Software Engineer I employer: Cerebras
Contact Detail:
Cerebras Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Engineer I
✨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 involving AI and cloud tech. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to LLMs and distributed systems. The more you rehearse, the more confident you'll feel!
✨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, we love seeing candidates who are proactive!
We think you need these skills to ace Staff Software Engineer I
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI systems and cloud technologies. We want to see how your skills align with our mission to build agentic AI experiences!
Showcase Your Technical Skills: Don’t hold back on detailing your software engineering foundations, especially in Python and any other languages you’re proficient in. We’re keen to know about your hands-on experience with distributed systems and LLM integration.
Communicate Clearly: Since this role involves influencing and aligning teams, make sure your application reflects your ability to explain complex concepts simply. We love candidates who can bridge the gap between technical and non-technical audiences!
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and get you into our recruitment process smoothly!
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.
✨Communicate Clearly
Since this role requires explaining complex concepts to both technical and non-technical stakeholders, practice articulating your thoughts clearly. Use simple language to describe your past projects and the architectural choices you made.
✨Show Your Leadership Skills
Even though this is an individual contributor role, demonstrate your ability to lead by sharing examples of how you've influenced teams or mentored engineers. Highlight your experience in raising engineering standards and promoting best practices.
✨Prepare for Scenario Questions
Expect questions that assess your problem-solving skills and decision-making process. Think of scenarios where you had to make trade-offs in design or handle technical risks, and be ready to explain your thought process and the outcomes.