At a Glance
- Tasks: Develop and engineer production-grade GenAI systems using Python and advanced technologies.
- Company: Join a leading global tech hub in Dublin or Belfast with a hybrid work model.
- Benefits: Enjoy a competitive salary, health benefits, and opportunities for professional growth.
- Other info: Be part of a collaborative team focused on cutting-edge AI technology.
- Why this job: Make a real impact by building innovative AI solutions in a dynamic environment.
- Qualifications: 6-10 years of Python experience, with expertise in RAG pipelines and data architecture.
The predicted salary is between 70000 - 90000 € per year.
Location: Dublin (OR) Belfast (Hybrid - 3 Days In-Office)
Role Type: Permanent / Full-Time (FTE)
Our client is looking for a Senior GenAI Application Developer/Engineer to join their global technology hub in Dublin. This is a high-impact, permanent role designed for a Python expert who can move beyond basic AI experimentation and into the engineering of production-grade, autonomous systems.
What our client is looking for:
- The Python Specialist: A developer with 6-10 years of professional experience. You must have 'under-the-hood' knowledge of Python, specifically for building high-throughput microservices and complex data pipelines using FastAPI, Pandas, and NumPy.
- The RAG & Agentic Expert: This is the 'Critical' requirement. Our client needs someone with deep hands-on experience building Retrieval-Augmented Generation (RAG) pipelines and Agentic frameworks. You should know how to use LangChain or LlamaIndex to create AI that can execute multi-step tasks.
- The Data Architect: Proficiency in Vector Databases is essential. You should be comfortable designing data persistence layers using PG Vector, Pinecone, Milvus, or Mongo Atlas to handle large amounts of unstructured data.
- The MLOps Engineer: You don't just write code; you ship it. Our client requires experience deploying GenAI models into production using Kubernetes (or OpenShift) and establishing robust CI/CD pipelines via Jenkins, GitLab, or Azure DevOps.
- The AI Safety Advocate: A working knowledge of Guardrails is key. You should understand how to assess the performance and safety of GenAI features to ensure they meet the rigorous standards of a global bank.
If you are interested then please apply or share your updated CV on yogeshwari.sen@randstad digital.com with your availability and I will give you a call back to discuss the role further.
Randstad Technologies Ltd is a leading specialist recruitment business for the IT & Engineering industries.
Please note that due to a high level of applications, we can only respond to applicants whose skills & qualifications are suitable for this position. No terminology in this advert is intended to discriminate against any of the protected characteristics that fall under the Equality Act 2010.
For the purposes of the Conduct Regulations 2003, when advertising permanent vacancies we are acting as an Employment Agency, and when advertising temporary/contract vacancies we are acting as an Employment Business.
Senior Python/GenAI Developer employer: Randstad Digital
Join a forward-thinking global technology hub in Dublin or Belfast, where innovation meets collaboration. Our client offers a dynamic work culture that prioritises employee growth through continuous learning and development opportunities, alongside a hybrid working model that promotes work-life balance. With a commitment to cutting-edge technology and a focus on impactful projects, this is an excellent opportunity for those looking to make a meaningful contribution in the field of AI and software engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Python/GenAI Developer
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with Python or GenAI. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving FastAPI, Pandas, and NumPy. This is your chance to demonstrate your expertise in building high-throughput microservices and complex data pipelines.
✨Tip Number 3
Prepare for technical interviews by brushing up on RAG pipelines and Agentic frameworks. Be ready to discuss how you've used LangChain or LlamaIndex in your past projects. We want you to shine!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Senior Python/GenAI Developer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your Python expertise and experience with GenAI. Use keywords from the job description to show we’re on the same page about what you bring to the table.
Showcase Relevant Projects:Include specific projects where you've built RAG pipelines or worked with vector databases. We want to see your hands-on experience, so don’t hold back on the details!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you’re excited about this role and how your skills align with our needs. Keep it conversational but professional.
Apply Through Our Website:We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any updates!
How to prepare for a job interview at Randstad Digital
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially around FastAPI, Pandas, and NumPy. Be ready to discuss specific projects where you've built high-throughput microservices or complex data pipelines, as this will show your depth of knowledge.
✨Showcase Your RAG Expertise
Prepare to talk about your hands-on experience with Retrieval-Augmented Generation (RAG) pipelines and Agentic frameworks. If you've used LangChain or LlamaIndex, have examples ready to demonstrate how you've executed multi-step tasks effectively.
✨Data Architecture is Key
Familiarise yourself with vector databases and be prepared to discuss how you've designed data persistence layers using PG Vector, Pinecone, Milvus, or Mongo Atlas. Highlight any challenges you faced and how you overcame them.
✨MLOps Experience Matters
Be ready to explain your experience in deploying GenAI models into production. Discuss your familiarity with Kubernetes or OpenShift and how you've established CI/CD pipelines using Jenkins, GitLab, or Azure DevOps. This will show that you can not only write code but also ship it successfully.
