At a Glance
- Tasks: Design and implement cutting-edge AI agents for real-world applications.
- Company: Join a forward-thinking tech company with a focus on innovation.
- Benefits: Enjoy competitive pay, remote work flexibility, and opportunities for growth.
- Other info: Collaborative environment with a strong emphasis on learning and development.
- Why this job: Be at the forefront of AI technology and make a tangible impact.
- Qualifications: Degree in Computer Science or related field; experience in AI systems required.
The predicted salary is between 60000 - 80000 € per year.
Job Details:
- Hours: Full Time
- Location: Fully remote (UK, Sweden, Malta, Hungary, Spain, or Poland).
- Contract: Permanent
What The Role Entails
- Agent And System: Design and implementation of autonomous and human‑in‑the‑loop AI agents for real‑world production use. Architect, develop, and deploy agents using modern frameworks. Design multi‑agent systems – roles, planning strategies, memory management, tool use, and workflow orchestration. Implement Retrieval Augmented Generation (RAG) and semantic search pipelines, including indexing strategies, retrieval policies, evaluation, and optimization. Design and implement microservices‑based architectures to support scalable AI workflows.
- Integration & Engineering: Design and deploy agents that function as user‑facing experiences or embedded components within distributed, service‑oriented architectures. Develop and integrate agent tools, APIs, and system connectors for seamless interaction with external services, data stores, and internal platforms. Ensure robust output validation and error handling across agent interactions. Implement prompt engineering best practices, guardrails, and validation techniques to reduce hallucinations and improve reliability.
- Production & Operations: Productionize agentic systems with end‑to‑end observability, including tracing, performance metrics, and feedback loops. Build evaluation harnesses and automated testing for agents, prompts, and workflows. Apply industry best practices around LLM safety, reliability, and governance. Continuously stay current with advances in agent frameworks, LLM tooling, and GenAI system patterns.
- Collaboration & Communication: Partner with product, engineering, and business stakeholders to define requirements and design intuitive human‑AI interaction patterns. Communicate complex technical concepts to both technical and non‑technical audiences. Document architectures, decisions, and best practices, and share knowledge with the wider team.
What We Ask Of You
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
- Proven experience building and deploying agentic AI systems in production environments.
- Strong proficiency in Python, including writing well‑structured, testable code and automated evaluations.
- Hands‑on experience with modern agent frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI).
- Solid understanding of RAG architectures, vector databases, and semantic retrieval techniques.
- Experience with cloud platforms (AWS preferred) and containerization technologies.
- Strong analytical and problem‑solving skills, with the ability to work independently and collaboratively.
- Ability to switch seamlessly between deep technical discussions and clear, business‑oriented explanations.
What’s in it for you?
Our employees benefit from generous packages, activities, and initiatives that foster excellence and innovation.
Agentic AI Engineer (GenAI) employer: Play'n GO
As an Agentic AI Engineer (GenAI) at our company, you will thrive in a fully remote environment that promotes flexibility and work-life balance across the UK, Sweden, Malta, Hungary, Spain, or Poland. We offer competitive compensation packages, a culture of innovation, and ample opportunities for professional growth, ensuring that you are supported in your career while contributing to cutting-edge AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Agentic AI Engineer (GenAI)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and agentic systems. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to AI engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
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 StudySmarter.
We think you need these skills to ace Agentic AI Engineer (GenAI)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Agentic AI Engineer role. Highlight your experience with AI systems, Python proficiency, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects:If you've worked on any cool AI projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to know what you've built and how it relates to the role. Links to GitHub or demos are a bonus!
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’s super easy – just follow the prompts and submit your materials!
How to prepare for a job interview at Play'n GO
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest agent frameworks and RAG architectures. Brush up on your Python skills and be ready to discuss how you've implemented these technologies in past projects. Being able to talk confidently about your technical experience will impress the interviewers.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled complex challenges in AI systems. Think about specific instances where you had to design multi-agent systems or implement robust error handling. This will demonstrate your analytical abilities and how you approach real-world problems.
✨Communicate Clearly and Effectively
Practice explaining complex concepts in simple terms. You might need to discuss technical details with non-technical stakeholders, so being able to bridge that gap is crucial. Use clear examples to illustrate your points during the interview.
✨Stay Current with Industry Trends
Familiarise yourself with the latest advancements in GenAI and agent frameworks. Mention any recent developments or tools you’ve explored, as this shows your commitment to continuous learning and staying ahead in the field.
