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- Tasks: Design and deploy advanced AI systems for complex decision-making in industrial settings.
- Company: Innovative tech firm focused on cutting-edge AI solutions.
- Benefits: Competitive salary, hands-on experience, and opportunity for international travel.
- Why this job: Make a real impact by building intelligent agents that solve technical challenges.
- Qualifications: Expertise in AI architectures, Python programming, and cloud deployment.
- Other info: Exciting opportunity to work onsite in Kuwait for the first 6-12 months.
The predicted salary is between 36000 - 60000 £ per year.
We are seeking a hands-on and qualified AI Agent Architect to design and deploy advanced Agentic AI systems—comprising task-specific autonomous tools governed by a master agent—to support complex technical decision-making in industrial environments. This is a high-impact individual contributor role for someone who can independently deliver full-stack intelligent agents that interpret natural language queries and generate precise, context-aware outputs by interacting with structured and unstructured data, APIs, and analytical engines.
Responsibilities
- Architect and develop a multi-agent AI framework where autonomous agents coordinate to solve domain-specific technical queries.
- Leverage LLMs, NLP, and tool-based reasoning to automate data extraction, analysis, and insight generation.
- Build agents capable of integrating with engineering tools, simulators, databases, and knowledge sources.
- Collaborate with domain experts to align agent behavior with technical expectations and constraints.
- Implement safeguards to ensure accuracy, traceability, and reliability of AI-generated outputs.
- Continuously optimize prompting, agent orchestration, and performance under real-world conditions.
Business trip to Kuwait for first 6-12 months. On-site.
Skills
Must have
- Demonstrated expertise in building Agentic AI architectures, using frameworks like LangChain, AutoGen, CrewAI, or custom stacks.
- Strong foundation in LLM-based NLP, prompt engineering, and context-aware reasoning.
- Advanced Python programming and experience deploying AI workflows in cloud or containerized environments.
- Ability to work with APIs, data models, and external toolchains across complex systems.
- Comfortable operating independently with minimal supervision in a cross-functional environment.
- Ready for a long-term business trip to Kuwait for first 6-12 months.
Nice to have
- Exposure to industrial domains such as energy, manufacturing, or heavy engineering.
- Understanding of vector databases, knowledge graphs, and retrieval-augmented generation.
- Familiarity with Azure or AWS development environments.
Certifications
- Azure AI Engineer or Azure Data Engineer certification is a plus.
- AWS experience is nice to have, but not required.
Industry Experience
Oil and gas domain experience is a strong advantage, especially familiarity with digital operations or engineering workflows. However, candidates with relevant AI system-building experience in other complex industries are encouraged to apply.
AI Agent Architect (onsite work in Kuwait) employer: Luxoft
Contact Detail:
Luxoft Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Agent Architect (onsite work in Kuwait)
✨Tip Number 1
Network like a pro! Reach out to industry professionals on LinkedIn or at local meetups. We can’t stress enough how important it is to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those involving Agentic AI architectures. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. We recommend practicing common interview questions related to AI and coding challenges to boost your confidence.
✨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 are genuinely interested in joining our team.
We think you need these skills to ace AI Agent Architect (onsite work in Kuwait)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI Agent Architect role. Highlight your experience with Agentic AI architectures and any relevant projects you've worked on. We want to see how your skills align with 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 perfect fit for this role. Don’t forget to mention your readiness for the business trip to Kuwait!
Showcase Your Technical Skills: Be sure to showcase your technical skills, especially in Python programming and LLM-based NLP. We love seeing examples of your work, so if you have any projects or GitHub repositories, include them in your application!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Luxoft
✨Know Your AI Frameworks
Make sure you’re well-versed in the frameworks mentioned in the job description, like LangChain and AutoGen. Be ready to discuss your hands-on experience with these tools and how you've used them to build Agentic AI architectures.
✨Showcase Your Python Skills
Since advanced Python programming is a must-have, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so brush up on your Python knowledge and be ready to explain your thought process.
✨Understand the Industrial Context
Familiarise yourself with the industrial domains relevant to the role, such as energy or manufacturing. Being able to relate your AI expertise to real-world applications in these fields will show that you understand the bigger picture.
✨Prepare for Real-World Scenarios
Expect questions about how you would optimise agent performance under real-world conditions. Think of examples from your past experiences where you had to troubleshoot or enhance AI systems, and be ready to share those stories.