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- Tasks: Design and deploy advanced AI systems for complex decision-making in industrial environments.
- Company: Leading tech firm focused on innovative AI solutions.
- Benefits: Competitive salary, travel opportunities, and professional growth.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Expertise in AI architectures and strong Python programming skills required.
- Other info: Exciting long-term business trip to Kuwait for hands-on experience.
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 (on-site) employer: Luxoft
Contact Detail:
Luxoft Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Agent Architect (on-site)
✨Tip Number 1
Network like a pro! Reach out to industry professionals on LinkedIn or attend relevant meetups. We can’t stress enough how personal connections can open doors that applications alone can’t.
✨Tip Number 2
Show off your skills in real-time! Consider building a portfolio of projects that showcase your expertise in AI architectures and frameworks. We love seeing practical examples of what you can do!
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past projects. We want to see how you think and solve problems, so practice articulating your thought process.
✨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’re always looking for passionate candidates who are ready to make an impact.
We think you need these skills to ace AI Agent Architect (on-site)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Agentic AI architectures and relevant frameworks. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise in LLMs and NLP!
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 the perfect fit for this role. We love seeing genuine enthusiasm and a clear understanding of the job.
Showcase Your Projects: If you've worked on any cool projects related to AI or engineering tools, make sure to mention them! We’re interested in real-world applications of your skills, so include links or descriptions that demonstrate your hands-on experience.
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!
How to prepare for a job interview at Luxoft
✨Know Your Tech Inside Out
Make sure you’re well-versed in the frameworks mentioned in the job description, like LangChain and AutoGen. Brush up on your Python skills and be ready to discuss how you've deployed AI workflows in cloud environments.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've architected multi-agent AI systems or solved complex technical queries. Be ready to explain your thought process and how you collaborated with domain experts to align agent behaviour with expectations.
✨Understand the Industry Context
Familiarise yourself with the industrial domains relevant to the role, such as energy or manufacturing. If you have experience in oil and gas, make sure to highlight it, as it could set you apart from other candidates.
✨Be Ready for Real-World Scenarios
Expect questions about optimising agent performance under real-world conditions. Think of specific instances where you implemented safeguards for accuracy and reliability in AI outputs, and be prepared to discuss them.
