At a Glance
- Tasks: Design and deploy cutting-edge AI systems using Large Language Models.
- Company: Fast-growing tech company at the forefront of AI and data innovation.
- Benefits: Competitive salary, bonus, hybrid work, and a modern engineering stack.
- Other info: Join a collaborative team focused on building scalable AI products.
- Why this job: Make a real-world impact by solving complex engineering problems in AI.
- Qualifications: Strong Python skills and experience with LLM frameworks like PyTorch or TensorFlow.
The predicted salary is between 60000 - 75000 € per year.
We’re partnering with a fast-growing technology company operating at the intersection of AI and large-scale data. They are building next-generation AI systems that help transform vast amounts of unstructured information into actionable insights in real time.
This is an opportunity for an experienced Machine Learning Engineer to work on production-grade AI systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks.
What You’ll Be Doing
- Design and deploy AI/ML systems using LLMs for reasoning, orchestration, and intelligent automation
- Build agent-based workflows coordinating complex tasks across multiple tools and data sources
- Develop scalable data pipelines capable of processing large-scale structured and unstructured datasets
- Create semantic search and retrieval systems using vector databases and embedding technologies
- Deliver production-ready APIs and microservices for real-time AI inference
- Improve model performance through evaluation, observability, prompt testing, and optimisation
- Collaborate closely with product, engineering, and intelligence teams to translate complex requirements into practical AI solutions
What We’re Looking For
- Strong Python engineering background with hands-on experience in PyTorch and/or TensorFlow
- Experience building production systems using LLM frameworks such as LangChain, LangGraph, AutoGen, or similar
- Expertise with RAG architectures, vector databases, embeddings, and semantic search
- Strong understanding of prompt engineering, fine-tuning, and foundation model integrations
- Experience with ML/LLMOps, monitoring, evaluation frameworks, and cost/performance optimisation
- Knowledge of distributed systems, microservices, streaming architectures, and cloud-native infrastructure
- Hands-on experience with Docker and infrastructure tooling such as Terraform or CloudFormation
- Ability to build scalable, reliable, and secure AI systems in production environments
What’s On Offer
- Opportunity to work on cutting-edge AI products with real-world impact
- Hybrid working environment with flexibility built into the culture
- Modern engineering stack and strong technical ownership
- Collaborative, mission-driven team environment
- Competitive compensation and benefits package
This role would suit someone who enjoys solving complex engineering problems, building scalable AI systems, and working on applied AI products beyond proof-of-concept stage.
Senior AI Engineer employer: ViVA Tech Talent
Join a dynamic technology company in Belfast that is at the forefront of AI innovation, where you will have the opportunity to work on transformative AI systems that turn unstructured data into actionable insights. With a hybrid working model, a collaborative culture, and a commitment to employee growth, this role offers not just competitive compensation but also the chance to make a real-world impact through cutting-edge projects. Embrace the flexibility and modern engineering practices that empower you to take ownership of your work while being part of a mission-driven team.
StudySmarter Expert Advice🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Network like a pro! Connect with folks in the AI and ML space on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and agentic AI. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML frameworks. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior AI Engineer role. Highlight your Python engineering background, experience with LLM frameworks, and any relevant projects you've worked on. We want to see how you can bring value to our team!
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 experience aligns with our mission at StudySmarter. Be sure to mention specific technologies or projects that relate to the job description.
Showcase Your Projects:If you've worked on any production-grade AI systems or have experience with RAG architectures, make sure to include those in your application. We love seeing real-world applications of your skills, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to submit all your materials in one go. Plus, we love seeing candidates who take the initiative!
How to prepare for a job interview at ViVA Tech Talent
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, PyTorch, and TensorFlow. Brush up on your experience with LLM frameworks like LangChain and RAG architectures, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled complex engineering problems. Think about how you’ve built scalable AI systems or improved model performance, and be ready to explain your thought process and the impact of your solutions.
✨Collaborate and Communicate
Since this role involves working closely with product and engineering teams, practice articulating your ideas clearly. Be prepared to discuss how you’ve collaborated in the past and how you can translate complex requirements into practical AI solutions.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI projects and their future direction. This shows your genuine interest in the role and helps you gauge if the company culture aligns with your values, especially regarding innovation and teamwork.
