At a Glance
- Tasks: Architect and maintain cutting-edge AI systems and workflows.
- Company: Join a forward-thinking tech company focused on responsible AI.
- Benefits: Attractive salary, flexible working options, and continuous learning opportunities.
- Other info: Exciting work environment with ample room for career advancement.
- Why this job: Be at the forefront of AI innovation and make a meaningful impact.
- Qualifications: Experience in AI systems and a passion for responsible technology.
The predicted salary is between 50000 - 70000 £ per year.
The key responsibilities will cover:
- Architect and implement/maintain agentic systems, autonomous agents, multi-agent pipelines, tool-use workflows, planning loops, and memory-augmented reasoning.
- Implement LLM observability, logging, tracing, evaluation pipelines, and guardrails to maintain quality and reliability in production AI systems.
- Advise on responsible AI deployment.
Engineer employer: Teksystems
As an innovative leader in AI technology, our company offers engineers a dynamic work environment where creativity and collaboration thrive. Located in a vibrant tech hub, we provide exceptional benefits, a strong commitment to employee development, and opportunities to work on cutting-edge projects that shape the future of AI. Join us to be part of a culture that values responsibility and excellence in deploying transformative solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Engineer
✨Tip Number 1
Network like a pro! Reach out to fellow engineers and industry professionals on LinkedIn or at meetups. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving agentic systems and AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practising common engineering interview questions and even doing mock interviews with friends or mentors.
✨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 about their job search!
We think you need these skills to ace Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience and skills that align with the Engineer role. We want to see how your background fits into architecting and implementing agentic systems, so don’t hold back on those details!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about responsible AI deployment and how you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects:If you've worked on any projects related to multi-agent pipelines or LLM observability, make sure to mention them! We’re keen to see practical examples of your work that demonstrate your skills and creativity in the field.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Teksystems
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies and methodologies mentioned in the job description. Brush up on agentic systems, multi-agent pipelines, and memory-augmented reasoning. Being able to discuss these topics confidently will show that you’re not just familiar with them, but that you can also contribute meaningfully.
✨Prepare Real-World Examples
Think of specific projects or experiences where you've implemented similar systems or faced challenges related to AI deployment. Be ready to share how you approached these situations, what tools you used, and the outcomes. This will help demonstrate your practical knowledge and problem-solving skills.
✨Understand Responsible AI Principles
Since advising on responsible AI deployment is part of the role, make sure you’re up to speed on ethical considerations and best practices in AI. Be prepared to discuss how you would ensure quality and reliability in production AI systems, as well as any frameworks or guidelines you follow.
✨Ask Insightful Questions
Interviews are a two-way street, so come armed with questions that show your interest in the company and the role. Ask about their current projects involving LLM observability or how they handle logging and tracing in their systems. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
